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+{"year":"2022","title":"(Commercial) Automatic Speech Recognition as a Tool in Sociolinguistic Research","authors":["N Markl - University of Pennsylvania Working Papers in …, 2022"],"snippet":"As speech datasets used in sociolinguistic research increase in size, laborious and time-intensive manual orthographic transcription is a challenge, limiting the amount of (transcribed) data which can be analysed. In this paper, I discuss the use of (commercial) …","url":["https://repository.upenn.edu/cgi/viewcontent.cgi?article=2163&context=pwpl"]}
+{"year":"2022","title":"2 Related Work","authors":["M Kasri, M Birjali, M Nabil, A Beni-Hssane, A El-Ansari…"],"snippet":"Word embedding aims to learn distributed vector representations of words by exploiting the existence of a huge amount of contextual information in a large text corpus using different techniques. This idea starts with [30]. They proposed a neural …","url":["https://journals.riverpublishers.com/index.php/JICTS/article/download/13885/14689?inline=1"]}
+{"year":"2022","title":"22 ZYX","authors":["MC Quadri, L Schaffner, P Ullrich"],"snippet":"As is the case with many people, my first direct lessons about failure and errors happened at kindergarten and school. In my case, it was primarily due to my (back then undiagnosed) ADHD and, since it wasn’t my mother tongue, my precarious …","url":["https://apria.artez.nl/wp-content/uploads/2022/12/APRIA-Issue-5-Print-Out-V10-1.pdf"]}
+{"year":"2022","title":"4 Touché Task 1: Conversational Argument Retrieval","authors":["A Bondarenko, M Fröbe, M Beloucif, L Gienapp…"],"snippet":"… Other argument retrieval systems, such as ArgumenText [40] and TARGER [9], use the larger Common Crawl, requiring additionally also argument … scenarios, based on billions of sentences from the Common Crawl, however, it still lacks a …","url":["https://9dok.net/document/y4w4p04v-touch%C3%A9-task-conversational-argument-retrieval.html"]}
+{"year":"2022","title":"5 The Role of Language Prediction Models in Contractual Interpretation: The Challenges and Future Prospects of GPT-3","authors":["M Katrak - Legal Analytics: The Future of Analytics in Law, 2022"],"snippet":"… For training GPT-3, researchers used the Common Crawl dataset, which constituted nearly a trillion words. The Common Crawl dataset contains petabytes of data collected over the years and includes webpage data, text extracts, and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=2NeSEAAAQBAJ&oi=fnd&pg=PT48&dq=commoncrawl&ots=lPkjRPXu5b&sig=pq4AW4fB8kV84NhHBTZk2NGs6o4"]}
+{"year":"2022","title":"\" Way back then\": A Data-driven View of 25+ years of Web Evolution","authors":["V Agarwal, N Sastry - arXiv preprint arXiv:2202.08239, 2022"],"snippet":"… For example, the use of historical crawls of the web such as the Common Crawl5. [30] is a brief history of web crawlers. [9] considers … Similarly, the common crawl12 represents a huge dataset of Web URLs and their content, that can provide …","url":["https://arxiv.org/pdf/2202.08239"]}
+{"year":"2022","title":"A California Effect For Artificial Intelligence","authors":["H Josephson"],"snippet":"… (Respectively, they used 4.9 terabytes of English and Chinese text and images, 1.56 trillion words compiled from various datasets, and a combination of English Wikipedia with ten years of Common Crawl data.) As the inconsistent units show …","url":["https://techhenzy.com/final-a-california-effect-for-artificial-intelligence/"]}
+{"year":"2022","title":"A code-mixed task-oriented dialog dataset for medical domain","authors":["S Dowlagar, R Mamidi - Computer Speech & Language, 2022"],"snippet":"In the healthcare domain, medical and patient interactions form a crucial part of the diagnosis. Initially, the AI models developed for healthcare centered only on monolingual data. However, such models do not cater to the multilingual regions …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000729"]}
+{"year":"2022","title":"A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition","authors":["Y Chen, J Mikkelsen, A Binder, C Alt, L Hennig - arXiv preprint arXiv:2204.04980, 2022"],"snippet":"Pre-trained language models (PLM) are effective components of few-shot named entity recognition (NER) approaches when augmented with continued pre-training on task-specific out-of-domain data or fine-tuning on in-domain data. However, their …","url":["https://arxiv.org/pdf/2204.04980"]}
+{"year":"2022","title":"A Comparative Study of Pre-trained Word Embeddings for Arabic Sentiment Analysis","authors":["M Zouidine, M Khalil - 2022 IEEE 46th Annual Computers, Software, and …, 2022"],"snippet":"In this paper, we conduct a series of experiments to systematically study both context-independent and context-dependent word embeddings for the purpose of Arabic sentiment analysis. We use pretrained word embeddings as fixed features extractors to provide …","url":["https://ieeexplore.ieee.org/abstract/document/9842526/"]}
+{"year":"2022","title":"A comparative study on vectorization methods for non-functional requirements classification","authors":["P Leelaprute, S Amasaki - Information and Software Technology, 2022"],"snippet":"… The pre-trained model with 840 billion tokens of Common Crawl was used. This study used a vectorization method [30] based on the … For fastText, the pre-trained model with Common Crawl and Wikipedia was used. This study also used a …","url":["https://www.sciencedirect.com/science/article/pii/S0950584922001239"]}
+{"year":"2022","title":"A Comparative Text Classification Study with Deep Learning-Based Algorithms","authors":["Ö Köksal, Ö Akgül - 2022 9th International Conference on Electrical and …, 2022"],"snippet":"… The vectors are trained from Wikipedia and Common Crawl, and each has a length of 300. Furthermore, the vectors are generated for n-grams, n length sequences of characters, instead of words. This property allows FastText to …","url":["https://ieeexplore.ieee.org/abstract/document/9772587/"]}
+{"year":"2022","title":"A Comparison of Approaches for Imbalanced Classification Problems in the Context of Retrieving Relevant Documents for an Analysis","authors":["S Wankmüller - arXiv preprint arXiv:2205.01600, 2022"],"snippet":"One of the first steps in many text-based social science studies is to retrieve documents that are relevant for the analysis from large corpora of otherwise irrelevant documents. The conventional approach in social science to address this …","url":["https://arxiv.org/pdf/2205.01600"]}
+{"year":"2022","title":"A COMPREHENSIVE ANALYSIS OF SUBWORD TOKENIZERS FOR MORPHOLOGICALLY RICH LANGUAGES","authors":["E Erkaya - 2022"],"snippet":"… The corpus contains 33 gigabyte (GB) of text which is obtained by filtering the Common Crawl corpus. As shown in Table 4.1, each tokenizer can produce different tokens for the same word. To compare the tokenizers, we used BOUN Treebank [30] …","url":["https://www.cmpe.boun.edu.tr/~gungort/theses/A%20Comprehensive%20Analysis%20of%20Subword%20Tokenizers%20for%20Morphologically%20Rich%20Languages.pdf"]}
+{"year":"2022","title":"A Comprehensive Survey of Natural Language Generation Advances from the Perspective of Digital Deception","authors":["K Jones, E Altuncu, VNL Franqueira, Y Wang, S Li - arXiv preprint arXiv:2208.05757, 2022"],"snippet":"… Common Crawl: The Common Crawl dataset is a massive collection of petabytes of web data currently hosted by Amazon (https://commoncrawl.… Due to its size, Common Crawl has been popularly used in the training and pre-training of many …","url":["https://arxiv.org/pdf/2208.05757"]}
+{"year":"2022","title":"A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches","authors":["A Mohammadi, R Ramezani, A Baraani - arXiv preprint arXiv:2212.04072, 2022"],"snippet":"… To decompose multi-hop question 𝑄 to simpler corpus 𝐷, First some candidate sub-question from a simple corpus 𝑆 will be created by mining 10M possible sub-questions from Common Crawl with a classifier. It then trains a decomposition model on the …","url":["https://arxiv.org/pdf/2212.04072"]}
+{"year":"2022","title":"A Corpus for Suggestion Mining of German Peer Feedback","authors":["R Rietsche, E Ritz, J Janda, D Pfütze"],"snippet":"Peer feedback in online education becomes increasingly important to meet the demand for feedback in large scale classes, such as eg Massive Open Online Courses (MOOCs). However, students are often not experts in how to write helpful …","url":["https://www.researchgate.net/profile/Roman-Rietsche/publication/362013990_A_Corpus_for_Suggestion_Mining_of_German_Peer_Feedback/links/62d10a069b8b7d1f6f712393/A-Corpus-for-Suggestion-Mining-of-German-Peer-Feedback.pdf"]}
+{"year":"2022","title":"A Critique Empirical Evaluation of Relevance Computation for Focused Web Crawlers","authors":["JDPNR Mary, S Balasubramanian, RSP Raj - Brazilian Archives of Biology and …, 2022"],"snippet":"HIGHLIGHTS This paper presents a survey on focused web crawlers. This paper presents the challenges in focused crawling research. This paper presents the highlights and hindrances of existing focused web crawlers. This paper also …","url":["https://www.scielo.br/j/babt/a/yG9Bw9htLXd554BfFcwwLCy/abstract/?lang=en"]}
+{"year":"2022","title":"A Data-driven Approach to Natural Language Processing for Contemporary and Historical French","authors":["PO Suarez - 2022"],"snippet":"… Each monthly Common Crawl snapshot is in itself a massive multilingual corpus, where every single file contains data coming from multiple web … Common Crawl has already been successfully used to train language models, even multilingual …","url":["https://tel.archives-ouvertes.fr/tel-03770337/document"]}
+{"year":"2022","title":"A Deep Learning approach to real-world Entity Linking: extracting and matching organisation mentions from unstructured text","authors":["T Bonomo - 2022"],"snippet":"… Specifically, the authors built a clean CommonCrawl Corpus composed of text scraped from the web in 100 different languages, amounting to around 2.5 TB of text data. The amount of data obviously varies from language to language, but Conneau …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/112889/master_Bonomo_Tommaso_2022.pdf?sequence=1"]}
+{"year":"2022","title":"A Dual Attention-Based Representation for the Detection of Abusive Language in Texts and Memes. Technical Report No. CCC-22-005","authors":["HJJ Vásquez - 2022"],"snippet":"… For word representation we used pretrained fastText embeddings [83], trained with subword information on Common Crawl, which have been recognized as useful for this task according to the study presented in [8]. All the non-BERT based DNNs …","url":["https://ccc.inaoep.mx/archivos/2021/CCC-22-005.pdf"]}
+{"year":"2022","title":"A Format-Aware Reducer for Scriptable Rewriting of PDF Files","authors":["P Anantharaman, S Cheung, N Boorman, ME Locasto"],"snippet":"Sanitizing untrusted input is a significant unsolved problem in defensive cybersecurity and input handling. Even if we assume that a safe, provably correct parser exists to validate the input syntax, processing logic may still require the …","url":["https://prashant.at/files/pdffixer.pdf"]}
+{"year":"2022","title":"A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication","authors":["AS Luccioni, F Corry, H Sridharan, M Ananny, J Schultz… - 2022"],"snippet":"… , given their sheer size (C4 represents 2.3 TB of data, whereas the Common Crawl has 139TB), filtering them is complex and time-consuming, … In practice, documenting and deprecating these datasets is akin to a game of whack-a-mole …","url":["https://facctconference.org/static/pdfs_2022/facct22-17.pdf"]}
+{"year":"2022","title":"A Gated Recurrent Unit based architecture for recognizing ontology concepts from biological literature","authors":["P Devkota, SD Mohanty, P Manda - BioData Mining, 2022"],"snippet":"Annotating scientific literature with ontology concepts is a critical task in biology and several other domains for knowledge discovery. Ontology based annotations can power large-scale comparative analyses in a wide range of applications ranging …","url":["https://biodatamining.biomedcentral.com/articles/10.1186/s13040-022-00310-0"]}
+{"year":"2022","title":"A generating model for Finnish nominal inflection using distributional semantics","authors":["A Nikolaev, YY Chuang, RH Baayen - 2022"],"snippet":"Finnish nouns are characterized by rich inflectional variation, with obligatory marking of case and number, with optional possessive suffixes and with the possibility of further cliticization. We present a model for the conceptualization of …","url":["https://psyarxiv.com/ndtv2/download"]}
+{"year":"2022","title":"A Holistic Approach to Undesired Content Detection in the Real World","authors":["T Markov, C Zhang, S Agarwal, T Eloundou, T Lee… - arXiv preprint arXiv …, 2022"],"snippet":"… PUB consists of around 90k public examples including both samples from academic datasets and Web data (Common Crawl) labeled by our annotators. SYN adds additional 69k curated synthetic examples. MIX contains all examples in SYN …","url":["https://arxiv.org/pdf/2208.03274"]}
+{"year":"2022","title":"A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model","authors":["I Lakim, E Almazrouei, IA Alhaol, M Debbah, J Launay - Challenges {\\&, 2022"],"snippet":"… We use Common Crawl (CC) for acquiring large amounts of web data. Each CC dump is on average around 10TB, and we discard it immediately after processing it. On average, it takes 24 hours to fully process a dump: we used 21 dumps from CC …","url":["https://openreview.net/pdf?id=B-lS3zH8Zq"]}
+{"year":"2022","title":"A Hybrid Deep Learning Approach to Detect Bangla Social Media Hate Speech","authors":["T Ghosh, AAK Chowdhury, M Banna, H Al, M Nahian… - Proceedings of International …, 2022"],"snippet":"Social media has become an integral part of our day-to-day life. In our activities or posts on social media, the presence of hate speech written in the native language or English has increased significantly. It often leads to the spread of negativity …","url":["https://link.springer.com/chapter/10.1007/978-981-19-2445-3_50"]}
+{"year":"2022","title":"A hybrid feature-based approach for classification of Fake News in Sinhala on social media","authors":["W Wijayarathna, S Jayalal"],"snippet":"… According to research work on evaluating the word embedding for the Sinhala language, FastText trained on the Common Crawl dataset is the best word embedding for Sinhala compared to the Pre-trained Facebook FastText model, Word2Vec, and …","url":["https://www.researchgate.net/profile/Shantha-Jayalal/publication/356842533_A_hybrid_feature-based_approach_for_classification_of_Fake_News_in_Sinhala_on_social_media/links/62d4f3a166bd1654d66edb11/A-hybrid-feature-based-approach-for-classification-of-Fake-News-in-Sinhala-on-social-media.pdf"]}
+{"year":"2022","title":"A Hybrid Phishing Detection System Using Deep Learning-based URL and Content Analysis","authors":["M Korkmaz, E Kocyigit, OK Sahingoz, B Diri - Elektronika ir Elektrotechnika, 2022"],"snippet":"… With a new dataset (1 million URLs, half of which was obtained from PhishTank and the rest from the CommonCrawl database, and the dataset contains 10,000 images) which researchers used in [21], CNN and LSTM were tested in Intelligent …","url":["https://www.eejournal.ktu.lt/index.php/elt/article/download/31197/15556"]}
+{"year":"2022","title":"A hybrid quantum approach to leveraging data from HTML tables","authors":["P Jiménez Aguirre, JC Roldán Salvador… - Knowledge and Information …, 2022","P Jiménez, JC Roldán, R Corchuelo - Knowledge and Information Systems, 2022"],"snippet":"… Unfortunately, a recent analysis of the 32.04 million domains in the November 2019 Common Crawl has revealed that only 11.92 million domains provide such tags [5], which means that there are roughly 20.12 million domains that do not …","url":["https://idus.us.es/bitstream/handle/11441/131991/Jim%C3%A9nez2022_Article_AHybridQuantumApproachToLevera.pdf?sequence=1&isAllowed=y","https://link.springer.com/article/10.1007/s10115-021-01636-7"]}
+{"year":"2022","title":"A Knowledge-Enhanced Adversarial Model for Cross-lingual Structured Sentiment Analysis","authors":["Q Zhang, J Zhou, Q Chen, Q Bai, J Xiao, L He - arXiv preprint arXiv:2205.15514, 2022"],"snippet":"… XLM-RoBERTa model is pre-trained on the 100 languages with 2.5TB of filtered CommonCrawl data. Moreover, [35] finetuned XLM-RoBERTa models on named-entity-recognition (NER) task with multilingual datasets. However, most existing works use one of …","url":["https://arxiv.org/pdf/2205.15514"]}
+{"year":"2022","title":"A Large and Diverse Arabic Corpus for Language Modeling","authors":["AR Ali, W Antoun"],"snippet":"… The Open Super-large Crawled ALMAnaCH coRpus (OSCAR) is a multi-lingual corpus, extracted from Common Crawl (CC) by performing … N-gram counts and language models from the common crawl. In Proceedings of the Language Resources …","url":["http://percipience.io/papers/14-A%20Large%20and%20Diverse%20Arabic%20Corpus%20for%20Language%20Modeling.pdf"]}
+{"year":"2022","title":"A LEGAL FRAMEWORK FOR ARTIFICIAL INTELLIGENCE FAIRNESS REPORTING","authors":["JQ Yap, E Lim - The Cambridge Law Journal"],"snippet":"Clear understanding of artificial intelligence (AI) usage risks and how they are being addressed is needed, which require proper and adequate corporate disclosure. We advance a legal framework for AI Fairness Reporting to which companies can and …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C2D73FBE9BB74E5D41DDA6BDCA208424/S0008197322000460a.pdf/legal_framework_for_artificial_intelligence_fairness_reporting.pdf"]}
+{"year":"2022","title":"A Lite Romanian BERT: ALR-BERT","authors":["DC Nicolae, RK Yadav, D Tufiş - Computers, 2022"],"snippet":"… OSCAR—OSCAR, or Open Super-large Crawled ALMAnaCH corpora, is a massive multilingual corpus derived from the Common Crawl corpus using language categorization and filtering [16]. There are approximately 11 GB of text in …","url":["https://www.mdpi.com/2073-431X/11/4/57/htm"]}
+{"year":"2022","title":"A Literature Survey of Recent Advances in Chatbots. Information 2022, 13, 41","authors":["G Caldarini, S Jaf, K McGarry - 2022"],"snippet":"… This led to the development of pretrained systems such as BERT (Bidirectional Encoder Representations from transformers) [39] and GPT (Generative Pre-trained Transformer), which were trained with huge language datasets, such as Wikipedia …","url":["https://www.researchgate.net/profile/Sardar-Jaf-2/publication/357839467_A_Literature_Survey_of_Recent_Advances_in_Chatbots/links/61e2ca739a753545e2d1d107/A-Literature-Survey-of-Recent-Advances-in-Chatbots.pdf"]}
+{"year":"2022","title":"A Longitudinal Study of Semantic Networks in Schizophrenia and other Psychotic Disorders using the Word Association Task","authors":["AS Pintos, CLM Hui, S De Deyne, C Cheung, WT Ko… - Schizophrenia Bulletin …, 2022"],"snippet":"Background and Hypothesis The underpinnings of language deviations in psychotic symptoms (eg, formal thought disorder, delusions) remains unclear. We examined whether the semantic networks underlying word associations are useful predictors of …","url":["https://academic.oup.com/schizbullopen/advance-article/doi/10.1093/schizbullopen/sgac054/6674699"]}
+{"year":"2022","title":"A Machine Learning approach for Fake News Detection.","authors":["WH Bisen, A Paunikar, B Thakur, A Garg, K Nangliya - International Journal of Next …, 2022"],"snippet":"A vital role is played by the media in the circulation of public information about the happenings. A fast spread of information using social media and social networks or websites is possible due to the quick development of the internet. With no worry …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=09765034&AN=160489051&h=vXvZ1C0skCEklVQHU1w%2BTwUttEuXD97YHxfGI7eP6GbTwor0eizcYbuqmIlDWIsykEHZBsH0ixNrZw%2BxAqBidQ%3D%3D&crl=c"]}
+{"year":"2022","title":"A mechanism for personalized Automatic Speech Recognition for less frequently spoken languages: the Greek case","authors":["P Antoniadis, E Tsardoulias, A Symeonidis"],"snippet":"Automatic Speech Recognition (ASR) has become increasingly popular since it significantly simplifies human-computer interaction, providing a more intuitive way of communication. Building an accurate, general-purpose ASR system is a challenging …","url":["https://panosantoniadis.github.io/files/personalized_asr.pdf"]}
+{"year":"2022","title":"A Multi-dimensional Evaluation of Tokenizer-free Multilingual Pretrained Models","authors":["J Sun, P Fernandes, X Wang, G Neubig - arXiv preprint arXiv:2210.07111, 2022"],"snippet":"… Both ByT5 and mT5 are pretrained on the multilingual Common Crawl (mC4) corpus1 using the span reconstruction objective proposed by Raffel et al. (2020). ByT5 operates on the raw UTF8 bytes of the input without any downsampling …","url":["https://arxiv.org/pdf/2210.07111"]}
+{"year":"2022","title":"A Multi-modal Approach to Mining Intent from Code-Mixed Hindi-English Calls in the Hyperlocal-Delivery Domain","authors":["J Mathew, P Sahu, B Singhal, A Joshi, KR Medikonda… - International Conference on …, 2022"],"snippet":"In this work we outline an approach to mine insights from calls between delivery partners (DP) and customers involved in hyperlocal food delivery in India. Incorrect addresses/ locations or other impediments prompt the DPs to call customers leading …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20980-2_41"]}
+{"year":"2022","title":"A Multi-task Multi-modal Framework for Sentiment and Emotion aided Cyberbully Detection","authors":["K Maity, A Kumar, S Saha - IEEE Internet Computing, 2022"],"snippet":"… The model uses a BERT based architecture pretrained by the Wikipedia and Common Crawl, along with PMINDIA and Dakshina corpora … So to overcome this issue, we have chosen MuRIL BERT, which has been pre-trained by Wikipedia and …","url":["https://ieeexplore.ieee.org/abstract/document/9733228/"]}
+{"year":"2022","title":"A Multilingual Approach to Scene Text Visual Question Answering","authors":["D Karatzas - Document Analysis Systems: 15th IAPR International …","J Brugués i Pujolràs, L Gómez i Bigordà, D Karatzas - International Workshop on …, 2022"],"snippet":"… The provided FastText embeddings are either trained on Wikipedia (Wiki) or Common Crawl (CC) corpora and are available in 157 languages Footnote 3 . We have used the monolingual embeddings trained in both Wiki and CC, and we have …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=81xwEAAAQBAJ&oi=fnd&pg=PA65&dq=commoncrawl&ots=vQu3SxHxPs&sig=P3my4WCb63x3Ok5GPvjtzpy_FcI","https://link.springer.com/chapter/10.1007/978-3-031-06555-2_5"]}
+{"year":"2022","title":"A Multilingual Simplified Language News Corpus","authors":["R Hauser, J Vamvas, S Ebling, M Volk - 2nd Workshop on Tools and Resources for …, 2022"],"snippet":"Simplified language news articles are being offered by specialized web portals in several countries. The thousands of articles that have been published over the years are a valuable resource for natural language processing, especially for efforts …","url":["https://cental.uclouvain.be/readi2022/readi_2022_proceedings.pdf#page=35"]}
+{"year":"2022","title":"A multistage retrieval system for health-related misinformation detection","authors":["M Fernández-Pichel, DE Losada, JC Pichel - Engineering Applications of Artificial …, 2022"],"snippet":"Web search is widely used to find online medical advice. As such, health-related information access requires retrieval algorithms capable of promoting reliable documents and filtering out unreliable ones. To this end, different types of …","url":["https://www.sciencedirect.com/science/article/pii/S0952197622002950"]}
+{"year":"2022","title":"A Novel Approach to Train Diverse Types of Language Models for Health Mention Classification of Tweets","authors":["PI Khan, I Razzak, A Dengel, S Ahmed - arXiv preprint arXiv:2204.06337, 2022"],"snippet":"Health mention classification deals with the disease detection in a given text containing disease words. However, non-health and figurative use of disease words adds challenges to the task. Recently, adversarial training acting as a means of …","url":["https://arxiv.org/pdf/2204.06337"]}
+{"year":"2022","title":"A Paradigm Shift from “Human Writing” to “Machine Generation” in Personality Test Development: an Application of State-of-the-Art Natural Language Processing","authors":["P Lee, S Fyffe, M Son, Z Jia, Z Yao - Journal of Business and Psychology, 2022"],"snippet":"Natural language processing (NLP) techniques have become increasingly popular in areas of psychological assessment. Recently, researchers have sought to use NLP techniques for automatic item generation (AIG) in the personality domain …","url":["https://link.springer.com/article/10.1007/s10869-022-09864-6"]}
+{"year":"2022","title":"A Part-of-Speech Tagger for Yiddish: First Steps in Tagging the Yiddish Book Center Corpus","authors":["S Kulick, N Ryant, B Santorini, J Wallenberg - arXiv preprint arXiv:2204.01175, 2022"],"snippet":"We describe the construction and evaluation of a part-of-speech tagger for Yiddish (the first one, to the best of our knowledge). This is the first step in a larger project of automatically assigning part-of-speech tags and syntactic structure to Yiddish text for …","url":["https://arxiv.org/pdf/2204.01175"]}
+{"year":"2022","title":"A Persian ASR-based SER: Modification of Sharif Emotional Speech Database and Investigation of Persian Text Corpora","authors":["A Yazdani, Y Shekofteh - arXiv preprint arXiv:2211.09956, 2022"],"snippet":"Speech Emotion Recognition (SER) is one of the essential perceptual methods of humans in understanding the situation and how to interact with others, therefore, in recent years, it has been tried to add the ability to recognize emotions to human-machine …","url":["https://arxiv.org/pdf/2211.09956"]}
+{"year":"2022","title":"A Projection-Based Asymmetric Similarity Measure for Distributional Semantic Models","authors":["R Das"],"snippet":"… We apply our model to GloVe vector representations (trained on the Common Crawl 42B corpus) of pairs of words taken from two databases on free association norms, and compute the correlation between the human responses and our model’s …","url":["https://riadas.github.io/files/6_804_Final_Project.pdf"]}
+{"year":"2022","title":"A Review on Phishing Websites Revealing through Machine Learning","authors":["AS Sengar, A Bhola, RK Shukla, A Gupta - … on System Modeling & Advancement in …, 2021"],"snippet":"Phishing is a frequent assault in which unsuspecting people’s unique, private, and sensitive information is stolen through fake websites. The primary objective of phishing websites’consistent resource allocators isto steal unique, private, and …","url":["https://ieeexplore.ieee.org/abstract/document/9676288/"]}
+{"year":"2022","title":"A Review on Text-Based Emotion Detection--Techniques, Applications, Datasets, and Future Directions","authors":["S Kusal, S Patil, J Choudrie, K Kotecha, D Vora… - arXiv preprint arXiv …, 2022"],"snippet":"Artificial Intelligence (AI) has been used for processing data to make decisions, interact with humans, and understand their feelings and emotions. With the advent of the internet, people share and express their thoughts on day-to-day activities and …","url":["https://arxiv.org/pdf/2205.03235"]}
+{"year":"2022","title":"A Roadmap for Big Model","authors":["S Yuan, H Zhao, S Zhao, J Leng, Y Liang, X Wang… - arXiv preprint arXiv …, 2022"],"snippet":"… C4 is a colossal, cleaned version of Common Crawl’s web crawl corpus. It is based on Common Crawl dataset and was used to train the … CLUECorpus2020 is a high-quality Chinese pre-training corpus obtained by cleaning the Chinese part of …","url":["https://arxiv.org/pdf/2203.14101"]}
+{"year":"2022","title":"A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation","authors":["Y Chen, F Wei, X Sun, Z Wu, S Lin - arXiv preprint arXiv:2203.04287, 2022"],"snippet":"This paper proposes a simple transfer learning baseline for sign language translation. Existing sign language datasets (eg PHOENIX-2014T, CSL-Daily) contain only about 10K-20K pairs of sign videos, gloss annotations and texts, which …","url":["https://arxiv.org/pdf/2203.04287"]}
+{"year":"2022","title":"A Study of Commonsense Reasoning with Language Models","authors":["RMR Branco - 2021"],"snippet":"Artificial Intelligence (AI) has gone through an increasing growth in the past decades, which in the present day translates to its usage in almost every sector of society. From its inception, AI pursues the reproduction of human intelligence. Currently, AI¬equipped …","url":["https://repositorio.ul.pt/bitstream/10451/51357/1/TM_Ruben_Branco.pdf"]}
+{"year":"2022","title":"A Study of Implicit Bias in Pretrained Language Models against People with Disabilities","authors":["PN Venkit, M Srinath, S Wilson - Proceedings of the 29th International Conference on …, 2022"],"snippet":"Pretrained language models (PLMs) have been shown to exhibit sociodemographic biases, such as against gender and race, raising concerns of downstream biases in language technologies. However, PLMs’ biases against people with disabilities (PWDs) …","url":["https://aclanthology.org/2022.coling-1.113.pdf"]}
+{"year":"2022","title":"A Study of Implicit Language Model Bias Against People With Disabilities","authors":["PN Venkit, M Srinath, S Wilson"],"snippet":"Pretrained language models (PLMs) have been shown to exhibit sociodemographic biases, such as against gender and race, raising concerns of downstream biases in language technologies. However, PLMs’ biases against people with disabilities (PWDs) …","url":["https://shomir.net/pdf/publications/coling_2022_pranav.pdf"]}
+{"year":"2022","title":"A Study of Various Word Embeddings in Deep Learning","authors":["P Shah, S Shah, S Joshi - 2022 3rd International Conference for Emerging …, 2022"],"snippet":"With the number of users and reviews rising on the internet, and the liberty was given to post anything on it, it is still a major issue to identify the sentiment of the reviews. The traditional machine learning models are taking a lot of computational …","url":["https://ieeexplore.ieee.org/abstract/document/9824963/"]}
+{"year":"2022","title":"A Study on Chinese-English Machine Translation Based on Transfer Learning and Neural Networks","authors":["C Li - Wireless Communications and Mobile Computing, 2022"],"snippet":"The existing Chinese-English machine translation has problems such as inaccurate word translation and difficult translation of long sentences. To this end, this paper proposes a new machine translation model based on bidirectional Chinese-English …","url":["https://www.hindawi.com/journals/wcmc/2022/8282164/"]}
+{"year":"2022","title":"A Study on Extracting Named Entities from Fine-tuned vs. Differentially Private Fine-tuned BERT Models","authors":["A Diera, N Lell, A Garifullina, A Scherp - arXiv preprint arXiv:2212.03749, 2022"],"snippet":"… During prompt creation, we sampled a 100 character length string either from the Common Crawl dataset (naive prompting) or from the test set (informed prompting). We set the sequence length to 256 tokens. We removed the tokens of the prompt …","url":["https://arxiv.org/pdf/2212.03749"]}
+{"year":"2022","title":"A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective","authors":["E Al-Hossami, S Shaikh - arXiv preprint arXiv:2202.04847, 2022"],"snippet":"In this survey paper, we overview major deep learning methods used in Natural Language Processing (NLP) and source code over the last 35 years. Next, we present a survey of the applications of Artificial Intelligence (AI) for source code, also …","url":["https://arxiv.org/pdf/2202.04847"]}
+{"year":"2022","title":"A Survey on Gender Bias in Natural Language Processing","authors":["K Stanczak, I Augenstein - arXiv preprint arXiv:2112.14168, 2021"],"snippet":"Language can be used as a means of reproducing and enforcing harmful stereotypes and biases and has been analysed as such in numerous research. In this paper, we present a survey of 304 papers on gender bias in natural language …","url":["https://arxiv.org/pdf/2112.14168"]}
+{"year":"2022","title":"A Survey on NLP resources, tools and techniques for Marathi Language Processing","authors":["P Lahoti, N Mittal, G Singh - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"… using goclassy architecture through language classiication and iltering the Common Crawl2 corpus. The current version of OSCAR corpus … CC-Net corpus applied an automatic pipeline to extract massive high-quality monolingual text from …","url":["https://dl.acm.org/doi/abs/10.1145/3548457"]}
+{"year":"2022","title":"A Survey on Phishing Website Detection Using Deep Neural Networks","authors":["V Sharma, T Halevi - International Conference on Human-Computer …, 2022"],"snippet":"Phishing is a social engineering attack, where an attacker poses as a legitimate individual or institution and convinces a victim to divulge their details through human interaction. There has been a steep rise in phishing cases across the globe. A report …","url":["https://link.springer.com/chapter/10.1007/978-3-031-19682-9_87"]}
+{"year":"2022","title":"A Survey on Semantics in Automated Data Science","authors":["U Khurana, K Srinivas, H Samulowitz - arXiv preprint arXiv:2205.08018, 2022"],"snippet":"Data Scientists leverage common sense reasoning and domain knowledge to understand and enrich data for building predictive models. In recent years, we have witnessed a surge in tools and techniques for {\\em automated machine learning} …","url":["https://arxiv.org/pdf/2205.08018"]}
+{"year":"2022","title":"A survey on text classification: Practical perspectives on the Italian language","authors":["A Gasparetto, A Zangari, M Marcuzzo, A Albarelli - PloS one, 2022"],"snippet":"Text Classification methods have been improving at an unparalleled speed in the last decade thanks to the success brought about by deep learning. Historically, state-of-the-art approaches have been developed for and benchmarked against English datasets …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0270904"]}
+{"year":"2022","title":"A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions","authors":["B Qin, B Hui, L Wang, M Yang, J Li, B Li, R Geng… - arXiv preprint arXiv …, 2022"],"snippet":"… WDC WebTables [79] is a large-scale table collection, which contains over 233 million tables and has been extracted from the July 2015 version of the CommonCrawl. Those tables are classified as either relational (90 million), entity (139 …","url":["https://arxiv.org/pdf/2208.13629"]}
+{"year":"2022","title":"A Symmetric Fusion Learning Model for Detecting Visual Relations and Scene Parsing","authors":["X Liu, X Jing, Z Zheng, W Du, X Ding, Q Zhu - Scientific Programming, 2022"],"snippet":"… We employ a pretrained word vector fastText trained on Common Crawl [38] to implement our purpose. Unlike the word vector models that ignore the morphological features inside words, the fastText model utilizes a bag of n-grams to …","url":["https://www.hindawi.com/journals/sp/2022/5985392/"]}
+{"year":"2022","title":"A Systematic Review on Machine Learning and Deep Learning Models for Electronic Information Security in Mobile Networks","authors":["C Gupta, I Johri, K Srinivasan, YC Hu, SM Qaisar… - Sensors, 2022"],"snippet":"Today’s advancements in wireless communication technologies have resulted in a tremendous volume of data being generated. Most of our information is part of a widespread network that connects various devices across the globe. The …","url":["https://www.mdpi.com/1424-8220/22/5/2017/pdf"]}
+{"year":"2022","title":"A thesis that writes itself: On the threat of AI-generated essays within academia","authors":["A Olsson, O Engelbrektsson - 2022"],"snippet":"… 3 The CommonCrawl dataset is a large dataset of web crawl data that is freely available. The dataset is made up of data from various web crawls and contains a wealth of information on the web. The dataset used by GPT-3 is 570GB. …","url":["https://www.diva-portal.org/smash/get/diva2:1669744/FULLTEXT02"]}
+{"year":"2022","title":"A Tool for Study on Impact of Big Data Technologies on firm performance","authors":["C Lotfi, S Srinivasan, M Ertz, I Latrous"],"snippet":"Organizations can use big data analytics to evaluate large data volumes and collect new information. It aids in answering basic inquiries concerning business operations and performance. It also aids in the discovery of unknown patterns in massive …","url":["https://www.researchgate.net/profile/Myriam-Ertz/publication/358504492_A_Tool_for_Study_on_Impact_of_Big_Data_Technologies_on_Firm_Performance/links/62053348634ff774f4c0b07c/A-Tool-for-Study-on-Impact-of-Big-Data-Technologies-on-Firm-Performance.pdf"]}
+{"year":"2022","title":"A Transferable and Automatic Tuning of Deep Reinforcement Learning for Cost Effective Phishing Detection","authors":["O Lavie, A Shabtai, G Katz - arXiv preprint arXiv:2209.09033, 2022"],"snippet":"… The first dataset is Bahnsen [16], which contains 1.2M benign URLs taken from the Common Crawl corpus, and 1.146M phishing URLs from PhishTank. The second dataset is Wang [19], which contains 245K phishing URLs collected from …","url":["https://arxiv.org/pdf/2209.09033"]}
+{"year":"2022","title":"A Transformer-based Sequence-labeling Approach to the Slovenian Cross-domain Automatic Term Extraction","authors":["THH Tran, M Martinc, A Repar, A Doucet, S Pollak"],"snippet":"Automatic term extraction (ATE) is a popular research task that eases the time and effort of manually identifying terms from domainspecific corpora by providing a list of candidate terms. In this paper, we treat terminology extraction as a sequence-labeling …","url":["https://nl.ijs.si/jtdh22/pdf/JTDH2022_Tran-et-al_A-Transformer-based-Sequence-labeling-Approach-to-the-Slovenian-Cross-domain-Automatic-Term-Extraction.pdf"]}
+{"year":"2022","title":"A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model","authors":["X Sun, T Ge, S Ma, J Li, F Wei, H Wang - arXiv preprint arXiv:2201.10707, 2022"],"snippet":"Synthetic data construction of Grammatical Error Correction (GEC) for non-English languages relies heavily on human-designed and language-specific rules, which produce limited error-corrected patterns. In this paper, we propose a generic and …","url":["https://arxiv.org/pdf/2201.10707"]}
+{"year":"2022","title":"A Universal Deduplication Architecture for Secure and Efficient Cloud Storage","authors":["K Saric, G Ramachandran, S Pal, R Jurdak, S Nepal - Proceedings of the Fourth IEEE …, 2022"],"snippet":"… Bloom filters populated with lists of filenames found in the Common Crawl dataset returned query responses in under 5 milliseconds on a typical laptop while configured with a false positive probability of 1 in 1015 (1 in a quadrillion) This is a …","url":["https://eprints.qut.edu.au/236903/1/Saric_A_Universal_Deduplication_Architecture.pdf"]}
+{"year":"2022","title":"A Use Case of Patent Classification Using Deep Learning with Transfer Learning","authors":["R Henriques, A Ferreira, M Castelli - Journal of Data and Information Science, 2022"],"snippet":"Abstract: Purpose: Patent classification is one of the areas in Intellectual Property Analytics (IPA), and a growing use case since the number of patent applications has been increasing worldwide. We propose using machine learning algorithms to …","url":["http://manu47.magtech.com.cn/Jwk3_jdis/EN/article/downloadArticleFile.do?attachType=PDF&id=441"]}
+{"year":"2022","title":"A User Study on Clarifying Comparative Questions","authors":["A Bondarenko, E Shirshakova, M Hagen - Proceedings of CHIIR, 2022"],"snippet":"… From the obtained entities, we selected the pairs with the highest sentence-wise co-occurrence frequencies in the Common Crawl snapshot 2014154 (eg, ‘drummer’ and ‘guitarist’ for occupation or ‘amoxicillin’ and ‘ciprofloxacin’ for antibiotics). As for …","url":["https://webis.de/downloads/publications/papers/bondarenko_2022b.pdf"]}
+{"year":"2022","title":"A Warm Start and a Clean Crawled Corpus--A Recipe for Good Language Models","authors":["V Snæbjarnarson, HB Símonarson, PO Ragnarsson… - arXiv preprint arXiv …, 2022"],"snippet":"… We also demonstrate how to directly extract Icelandic text from the Common Crawl corpus in … that in mC4, which is also sourced from Common Crawl, there are 107 labelled languages, with … We believe that by using text extracted from the …","url":["https://arxiv.org/pdf/2201.05601"]}
+{"year":"2022","title":"A Web-Scale Analysis of the Community Origins of Image Memes","authors":["D Morina, MS Bernstein - Proceedings of the ACM on Human-Computer …, 2022"],"snippet":"… So, we adopted a common revision called harmonic centrality [43], endorsed and used by the Common Crawl foundation in their web-wide web crawl snapshot [13]. We obtained harmonic centrality scores for each community from a full web crawl by …","url":["https://dl.acm.org/doi/abs/10.1145/3512921"]}
+{"year":"2022","title":"Abstractive Summarization of Broadcast News Stories for Estonian","authors":["H Henry, A Tanel"],"snippet":"We present an approach for generating abstractive summaries for Estonian spoken news stories in a low-resource setting. Given a recording of a radio news story, the goal is to create a summary that captures the essential information in a short format …","url":["https://www.bjmc.lu.lv/fileadmin/user_upload/lu_portal/projekti/bjmc/Contents/10_3_23_Harm.pdf"]}
+{"year":"2022","title":"Accurate Dependency Parsing and Tagging of Latin","authors":["S Nehrdich, O Hellwig"],"snippet":"Having access to high-quality grammatical annotations is important for downstream tasks in NLP as well as for corpus-based research. In this paper, we describe experiments with the Latin BERT word embeddings that were recently be made …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/LT4HALA/pdf/2022.lt4hala2022-1.3.pdf"]}
+{"year":"2022","title":"Accurately Identifying Cerebroarterial Stenosis from Angiography Reports Using Natural Language Processing Approaches","authors":["CH Lin, KC Hsu, CK Liang, TH Lee, CS Shih, YC Fann - Diagnostics, 2022"],"snippet":"Patients with intracranial artery stenosis show high incidence of stroke. Angiography reports contain rich but underutilized information that can enable the detection of cerebrovascular diseases. This study evaluated various natural language …","url":["https://www.mdpi.com/2075-4418/12/8/1882/pdf?version=1659537394"]}
+{"year":"2022","title":"Active Exploration based on Information Gain by Particle Filter for Efficient Spatial Concept Formation","authors":["A Taniguchi, Y Tabuchi, T Ishikawa, LE Hafi… - arXiv preprint arXiv …, 2022"],"snippet":"Autonomous robots are required to actively and adaptively learn the categories and words of various places by exploring the surrounding environment and interacting with users. In semantic mapping and spatial language acquisition conducted using …","url":["https://arxiv.org/pdf/2211.10934"]}
+{"year":"2022","title":"Ad creative generation using reinforced generative adversarial network","authors":["S Terzioğlu, KN Çoğalmış, A Bulut - Electronic Commerce Research, 2022"],"snippet":"… T5 and PEGASUS models were trained on 750 GB of English-language text from the public Common Crawl web scrape. BART model was trained on the CNN/Daily Mail dataset, which contains over 300k unique news articles from CNN and the Daily …","url":["https://link.springer.com/article/10.1007/s10660-022-09564-6"]}
+{"year":"2022","title":"Adam Mickiewicz University at WMT 2022: NER-Assisted and Quality-Aware Neural Machine Translation","authors":["A Nowakowski, G Pałka, K Guttmann, M Pokrywka - arXiv preprint arXiv:2209.02962, 2022"],"snippet":"This paper presents Adam Mickiewicz University's (AMU) submissions to the constrained track of the WMT 2022 General MT Task. We participated in the Ukrainian $\\leftrightarrow$ Czech translation directions. The systems are a weighted …","url":["https://arxiv.org/pdf/2209.02962"]}
+{"year":"2022","title":"Adam mickiewicz university's english-hausa submissions to the wmt 2021 news translation task","authors":["A Nowakowski, T Dwojak - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"This paper presents the Adam Mickiewicz University’s (AMU) submissions to the WMT 2021 News Translation Task. The submissions focus on the English↔ Hausa translation directions, which is a low-resource translation scenario between distant …","url":["https://aclanthology.org/2021.wmt-1.14.pdf"]}
+{"year":"2022","title":"Adapting Automatic Speech Recognition to the Radiology Domain for a Less-Resourced Language: The Case of Latvian","authors":["N Gruzitis, R Dargis, VJ Lasmanis, G Garkaje, D Gosko - Intelligent Sustainable …, 2022"],"snippet":"Automatic speech recognition (ASR) is becoming available to more and more languages. Training a quality ASR system typically requires significant amount of language resources—representative speech and text corpora. Recent advances in …","url":["https://link.springer.com/chapter/10.1007/978-981-16-6309-3_27"]}
+{"year":"2022","title":"Adapting Pretrained Models for Machine Translation","authors":["A Kurniawan - 2022"],"snippet":"Pre-trained language models received extensive attention in recent years. However, it is still challenging to incorporate a pre-trained model such as BERT into natural language generation tasks. This work investigates a recent method called adapters …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/175352/120426661.pdf?sequence=1"]}
+{"year":"2022","title":"Adapting Pretrained Text-to-Text Models for Long Text Sequences","authors":["W Xiong, A Gupta, S Toshniwal, Y Mehdad, W Yih - arXiv preprint arXiv:2209.10052, 2022"],"snippet":"We present an empirical study of adapting an existing pretrained text-to-text model for long-sequence inputs. Through a comprehensive study along three axes of the pretraining pipeline -- model architecture, optimization objective, and pretraining …","url":["https://arxiv.org/pdf/2209.10052"]}
+{"year":"2022","title":"Adapting Transformers for Multi-Label Text Classification","authors":["H Fallah, P Bellot, E Bruno, E Murisasco - 2022"],"snippet":"… , in addition to text crawled from the internet (Common-Crawl), on wikipedia article and books, thus getting more vocabulary coverage of MFHAD than CamemBERT that is pre-trained on a corpus derived from Common-Crawl. The …","url":["http://ceur-ws.org/Vol-3178/CIRCLE_2022_paper_07.pdf"]}
+{"year":"2022","title":"Addressing religious hate online: from taxonomy creation to automated detection","authors":["A Ramponi, B Testa, S Tonelli, E Jezek - PeerJ Computer Science, 2022"],"snippet":"… et al., 2020), a RoBERTa-based model pretrained on 2.5TB of CommonCrawl raw text containing 100 languages. We use the bert-base-multilingual-cased … OSCAR is a large-scale multilingual corpus based on filtered Common Crawl data that has …","url":["https://peerj.com/articles/cs-1128/"]}
+{"year":"2022","title":"Adversarial Cross-domain Community Question Retrieval","authors":["A Guo, X Li, N Pang, X Zhao - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"… In practice, we choose the embedding set (Common Crawl, glove.840B.300d), which contains 840B tokens and 2.2M vocabulary. The word embeddings are of 300 dimensions. The word embedding is updated during the training process. …","url":["https://dl.acm.org/doi/abs/10.1145/3487291"]}
+{"year":"2022","title":"AfriBERTa: Towards Viable Multilingual Language Models for Low-resource Languages","authors":["K Ogueji - 2022"],"snippet":"… Given that there is significant overlap between the African language corpora in Common Crawl and the BBC News data that we crawled, we … We observe that the quality of the dataset from Common Crawl is very low, confirming recent findings …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18662/Ogueji_Kelechi.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"AfroLID: A Neural Language Identification Tool for African Languages","authors":["I Adebara, AR Elmadany, M Abdul-Mageed, AA Inciarte - arXiv preprint arXiv …, 2022"],"snippet":"Language identification (LID) is a crucial precursor for NLP, especially for mining web data. Problematically, most of the world's $7000$+ languages today are not covered by LID technologies. We address this pressing issue for Africa by …","url":["https://arxiv.org/pdf/2210.11744"]}
+{"year":"2022","title":"AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages","authors":["BFP Dossou, AL Tonja, O Yousuf, S Osei, A Oppong… - arXiv preprint arXiv …, 2022"],"snippet":"In recent years, multilingual pre-trained language models have gained prominence due to their remarkable performance on numerous downstream Natural Language Processing tasks (NLP). However, pre-training these large multilingual language …","url":["https://arxiv.org/pdf/2211.03263"]}
+{"year":"2022","title":"AI Personification: Estimating the Personality of Language Models","authors":["SR Karra, S Nguyen, T Tulabandhula - arXiv preprint arXiv:2204.12000, 2022"],"snippet":"… GPT-3 was pretrained on an open-source dataset called Common Crawl, and other text corpora from sources such as Wikipedia (a popular online encyclopedia). TransformerXL: TransformerXL is a transformer-based language model capable of …","url":["https://arxiv.org/pdf/2204.12000"]}
+{"year":"2022","title":"AI WITH ALIEN CONTENT AND ALIEN METASEMANTICS","authors":["H Cappelen, J Dever"],"snippet":"… by the Common Crawl archiving service. Give the role that the Common Crawl database plays in the training of GPT-3, maybe the Common Crawl … in some way we can’t fully comprehend) by the way in which Common Crawl extracts and stores …","url":["https://hermancappelen.net/docs/AIAlienMetasemantics.pdf"]}
+{"year":"2022","title":"AI-based Structured Web Data Extraction","authors":["J Joneš - 2022"],"snippet":"In this thesis, we explore current approaches for automatic web data extraction, define their limitations, and aim to overcome them. We propose a deep learning model to extract structured data from graph and visual representations of web pages …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/174143/120418601.pdf?sequence=1"]}
+{"year":"2022","title":"AI-supported Natural Language Processing in project management–capabilities and research agenda","authors":["H NUHN, A OSWALD, A FLORE, R LANG"],"snippet":"AI-based natural language processing (NLP) models show remarkable performance in tasks like question answering or text generation in general. We argue that recent NLP-AI models will play a major role in the transformation of our societies, an …","url":["https://www.researchgate.net/profile/Helge-Nuhn/publication/361439333_AI-supported_Natural_Language_Processing_in_project_management_-capabilities_and_research_agenda/links/62b1979189e4f1160c8fde4d/AI-supported-Natural-Language-Processing-in-project-management-capabilities-and-research-agenda.pdf"]}
+{"year":"2022","title":"ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification","authors":["K North, M Zampieri, T Ranasinghe - arXiv preprint arXiv:2209.09034, 2022"],"snippet":"Lexical simplification (LS) is the task of automatically replacing complex words for easier ones making texts more accessible to various target populations (eg individuals with low literacy, individuals with learning disabilities, second language …","url":["https://arxiv.org/pdf/2209.09034"]}
+{"year":"2022","title":"Algal bloom monitoring using multi-spectral satellite data","authors":["D Grendaitė, L Petkevičius - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148380852/148380852.pdf"]}
+{"year":"2022","title":"Aligning Word Vectors on Low-Resource Languages with Wiktionary","authors":["M Izbicki - Proceedings of the Fifth Workshop on Technologies for …, 2022"],"snippet":"… these languages are of particular interest to the Wiktionary community for their historical importance, and thus have a lot of entries; but their historical nature also means there are few webpages written in these languages, and so the word vectors …","url":["https://aclanthology.org/2022.loresmt-1.14.pdf"]}
+{"year":"2022","title":"An Analysis of Social Biases Present in BERT Variants Across Multiple Languages","authors":["A Milios, P BehnamGhader - arXiv preprint arXiv:2211.14402, 2022"],"snippet":"… GreekBERT [15] is trained on the Greek Wikipedia, the Greek portion of Oscar [16] (a filtered and cleaned multilingual version of the Common Crawl dataset), and the Greek portion of the European Parliament Proceedings Parallel Corpus [17] …","url":["https://arxiv.org/pdf/2211.14402"]}
+{"year":"2022","title":"An Approach to Generate Realistic HTTP Parameters for Application Layer Deception","authors":["M Sahin, C Hébert, R Cabrera Lozoya - International Conference on Applied …, 2022"],"snippet":"… While the names of the honey HTML elements are ideally chosen by the user, authors also implement a suggestion tool based on a Markov model of URLs gathered from the Common Crawl [2] dataset. However, the paper does not provide …","url":["https://link.springer.com/chapter/10.1007/978-3-031-09234-3_17"]}
+{"year":"2022","title":"An Automatic Speech Recognition System for Bengali Language based on Wav2Vec2 and Transfer Learning","authors":["TT Showrav - arXiv preprint arXiv:2209.08119, 2022"],"snippet":"An independent, automated method of decoding and transcribing oral speech is known as automatic speech recognition (ASR). A typical ASR system extracts featured from audio recordings or streams and run one or more algorithms to map …","url":["https://arxiv.org/pdf/2209.08119"]}
+{"year":"2022","title":"An empirical study of the impact of log parsers on the performance of log-based anomaly detection","authors":["Y Fu, M Yan, Z Xu, X Xia, X Zhang, D Yang - Empirical Software Engineering, 2023"],"snippet":"… The word vectors are pre-trained on the Common Crawl Corpus dataset, and the dimension of word vectors is 300. Secondly, it uses the TF-IDF weight to sum up all word vectors in a log event to generate the log event vector. At the same time, the …","url":["https://link.springer.com/article/10.1007/s10664-022-10214-6"]}
+{"year":"2022","title":"An Empirical Study on the Fairness of Pre-trained Word Embeddings","authors":["E Sesari, M Hort, F Sarro - 2022"],"snippet":"… from 42 billion and 840 billion tokens of Common Crawl corpus. Pre-trained embeddings trained on … + UMBCWeb Base + statmt.org News and 600 billion tokens from Common Crawl. … Also according to these data, we can infer that …","url":["https://discovery.ucl.ac.uk/id/eprint/10149529/1/ACL___Word_Embedding_Bias.pdf"]}
+{"year":"2022","title":"An Ensemble Approach to Acronym Extraction using Transformers","authors":["P Sharma, H Saadany, L Zilio, D Kanojia, C Orasan - 2022"],"snippet":"… 2019) is a multilingual contextualised Language Model (LM) pre-trained on filtered CommonCrawl data from 100+ languages. Each … feed-forward hidden states, 8 heads; and is pre-trained on CommonCrawl data in over 100 languages …","url":["https://dipteshkanojia.github.io/files/sdu-ST-aaai-2022-acronym.pdf"]}
+{"year":"2022","title":"An ensemble multilingual model for toxic comment classification","authors":["G Xie - … Conference on Algorithms, Microchips and Network …, 2022"],"snippet":"… Unlabeled text in 100 languages is extracted from CommonCrawl datasets, totaling 2.5TB of text. It is trained in a RoBERTa fashion, that is, only using the MLM objective. XLM-R is a transformer-based multilingual masked language model pre-trained …","url":["https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12176/121761P/An-ensemble-multilingual-model-for-toxic-comment-classification/10.1117/12.2636419.full"]}
+{"year":"2022","title":"An Ensemble of Arabic Transformer-based Models for Arabic Sentiment Analysis","authors":["I El Karfi, S El Fkihi"],"snippet":"In recent years, sentiment analysis has gained momentum as a research area. This task aims at identifying the opinion that is expressed in a subjective statement. An opinion is a subjective expression describing personal thoughts and feelings. These …","url":["https://search.proquest.com/openview/ad34f3c57aa402f7589c6884ff93cbaf/1?pq-origsite=gscholar&cbl=5444811"]}
+{"year":"2022","title":"An ensemble transformer-based model for Arabic sentiment analysis","authors":["O Mohamed, AM Kassem, A Ashraf, S Jamal… - Social Network Analysis and …, 2023"],"snippet":"… XLM-R is a multilingual MLM trained on 2.5 TB of clean Common Crawl data in 100 languages. It provides a solid improvement over previous multilingual models such as mBERT. It performs well in various tasks such as classification, sequence …","url":["https://link.springer.com/article/10.1007/s13278-022-01009-0"]}
+{"year":"2022","title":"An image and text-based multimodal model for detecting fake news in OSN's","authors":["SK Uppada, P Patel - Journal of Intelligent Information Systems, 2022"],"snippet":"… RoBERTa is pre-trained on Books Corpus and English Wikipedia; in addition to this dataset, RoBERTa is trained on CommonCrawl, Web text corpus, and stories from Common Crawl datasets. A dense output layer with softmax as an activation …","url":["https://link.springer.com/article/10.1007/s10844-022-00764-y"]}
+{"year":"2022","title":"An Information Minimization Based Contrastive Learning Model for Unsupervised Sentence Embeddings Learning","authors":["S Chen, J Zhou, Y Sun, L He - arXiv preprint arXiv:2209.10951, 2022"],"snippet":"Unsupervised sentence embeddings learning has been recently dominated by contrastive learning methods (eg, SimCSE), which keep positive pairs similar and push negative pairs apart. The contrast operation aims to keep as much information …","url":["https://arxiv.org/pdf/2209.10951"]}
+{"year":"2022","title":"An integrated data framework for policy guidance during the coronavirus pandemic: Towards real-time decision support for economic policymakers","authors":["JO Dörr, J Kinne, D Lenz, G Licht, P Winker - PloS one, 2022"],"snippet":"… Specifically, XLM-RoBERTa has been trained on more than two terabyte of filtered common-crawl data [39]. It has acquired its basic language understanding using the masked language model approach [40], ie given a sequence of text—eg a …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263898"]}
+{"year":"2022","title":"An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective","authors":["A Rathore, S Dev, V Srikumar, JM Phillips, Y Zheng… - NeurIPS 2021 Competitions …, 2022"],"snippet":"Abstract Language representations are known to encode and propagate biases, ie, stereotypical associations between words or groups of words that may cause representational harm. In this demo, we utilize interactive visualization to increase …","url":["https://proceedings.mlr.press/v176/rathore22a/rathore22a.pdf"]}
+{"year":"2022","title":"An Interpretable Word Sense Classifier for Human Explainable Chatbot","authors":["RK Yadav, L Jiao, OC Granmo, M Goodwin - International Conference on Agents and …, 2022"],"snippet":"… The three models employ static embedding obtained from two sources, CommonCrawl and Base, and are trained using 1 layer neural network … This is because of the enriched information in CommonCrawl in comparison to Base word …","url":["https://link.springer.com/chapter/10.1007/978-3-031-10161-8_13"]}
+{"year":"2022","title":"An Unsupervised Approach to Genuine Health Information Retrieval Based on Scientific Evidence","authors":["R Upadhyay, G Pasi, M Viviani - International Conference on Web Information …, 2022"],"snippet":"… The original dataset is constituted by CommonCrawl news, Footnote 21 sampled from January, 1st 2020 to April 30th, 2020, which contains health-related news articles from all over the world. For our experiments, given the large volume of the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20891-1_10"]}
+{"year":"2022","title":"Analysing Environmental Narratives Computationally","authors":["RS Purves, O Koblet, B Adams - Unlocking Environmental Narratives: Towards …, 2022"],"snippet":"This book’s origins lie in a desire to showcase, through an interdisciplinary approach, the potential for computational methods in analysing text that describes the environment. Our argument is that these computational methods need not be …","url":["https://ubiquitypress.com/site/chapters/10.5334/bcs.c/download/5953/"]}
+{"year":"2022","title":"Analysis and Application of Language Models to Human-Generated Textual Content","authors":["M Di Giovanni - 2022"],"snippet":"… The authors trained the model on corpora of different sizes; the larger includes 42 billion tokens of web data from Common Crawl, tokenized and lowercased. A clear correlation between corpus size and performance is observed for syntactic tasks but …","url":["http://amsdottorato.unibo.it/10057/1/Tesi%20con%20Frontespizio.pdf"]}
+{"year":"2022","title":"Analysis and control of online interactions through neural natural language processing","authors":["L Laugier - 2022"],"snippet":"Natural Language Processing is motivated by applications where computers should gain a semantic and syntactic understanding of human language. Recently, the field has been impacted by a paradigm shift. Deep learning architectures coupled with …","url":["https://theses.hal.science/tel-03884481/document"]}
+{"year":"2022","title":"Analysis of Scientific Literature of LDOW Workshops: A Scientometric and NLP approach","authors":["S Shekarpour"],"snippet":"This paper contributes to compiling and publishing a structured dataset from the scientific literature of the Linked Data on the Web (LDOW) workshop series. This workshop was the primary venue for publishing the frontier topics related to …","url":["https://www.researchgate.net/profile/Enayat-Rajabi/publication/358973156_Analysis_of_Scientific_Literature_of_LDOW_Workshops_A_Scientometric_and_NLP_approach/links/62201e29c4c4fa27cd236da6/Analysis-of-Scientific-Literature-of-LDOW-Workshops-A-Scientometric-and-NLP-approach.pdf"]}
+{"year":"2022","title":"Analysis of Semantic Shift Before and After COVID-19 in Spanish Diachronic Word Embeddings","authors":["ER Betancourt, EC Murillo - 2022 XVLIII Latin American Computer Conference …, 2022"],"snippet":"… Como origen de los datos se usó el proyecto CommonCrawl (https://commoncrawl.org/), el cual regularmente recolecta documentos de … Se descargaron desde CommonCrawl los documentos correspondientes a la semana 51 del 2018 y la …","url":["https://ieeexplore.ieee.org/abstract/document/9959896/"]}
+{"year":"2022","title":"Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models","authors":["A Sboev, S Sboeva, I Moloshnikov, A Gryaznov… - Applied Sciences, 2022"],"snippet":"The paper presents the full-size Russian corpus of Internet users’ reviews on medicines with complex named entity recognition (NER) labeling of pharmaceutically relevant entities. We evaluate the accuracy levels reached on this …","url":["https://www.mdpi.com/2076-3417/12/1/491/pdf"]}
+{"year":"2022","title":"Analysis of the Semantic Vector Space Induced by a Neural Language Model and a Corpus","authors":["X Chen, J Hůla, A Dvořák - 2022"],"snippet":"… The language model that we use for this study is XLM-RoBERTa [1], which is a transformer-based model pre-trained on a large corpus (2.5TB of filtered CommonCrawl data) in a self-supervised fashion. The model uses a tokenizer based on …","url":["http://ceur-ws.org/Vol-3226/paper12.pdf"]}
+{"year":"2022","title":"Analysis of Word-level Embeddings for Indic Languages on AI4Bharat-IndicNLP Corpora","authors":["D Goswami, S Malviya, R Mishra, US Tiwary - 2021 IEEE 8th Uttar Pradesh Section …, 2021"],"snippet":"This paper presents the analysis of non-contextual word embeddings trained on AI4Bharat-IndicNLP corpus containing 2.7 billion words covering 10 Indian languages. We share the pre-trained embeddings for research and development in …","url":["https://ieeexplore.ieee.org/abstract/document/9667615/"]}
+{"year":"2022","title":"Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics","authors":["V Sanca, A Ailamaki - arXiv preprint arXiv:2212.07517, 2022"],"snippet":"As modern data pipelines continue to collect, produce, and store a variety of data formats, extracting and combining value from traditional and context-rich sources such as strings, text, video, audio, and logs becomes a manual process where such …","url":["https://arxiv.org/pdf/2212.07517"]}
+{"year":"2022","title":"Analyzing Antisemitism and Islamophobia using a Lexicon-based Approach","authors":["M Ali, S Zannettou - Workshop Proceedings of the 16th International AAAI …, 2022"],"snippet":"The spread of Antisemitic and Islamophobic content in a longstanding problem, in particular within fringe Web communities. In this work, we attempt to analyze the spread of Antisemitic and Islamophobic content on 4chan’s Politically Incorrect …","url":["https://workshop-proceedings.icwsm.org/pdf/2022_61.pdf"]}
+{"year":"2022","title":"Analyzing Gender Representation in Multilingual Models","authors":["H Gonen, S Ravfogel, Y Goldberg - arXiv preprint arXiv:2204.09168, 2022"],"snippet":"Multilingual language models were shown to allow for nontrivial transfer across scripts and languages. In this work, we study the structure of the internal representations that enable this transfer. We focus on the representation of gender …","url":["https://arxiv.org/pdf/2204.09168"]}
+{"year":"2022","title":"Analyzing the Mono-and Cross-Lingual Pretraining Dynamics of Multilingual Language Models","authors":["T Blevins, H Gonen, L Zettlemoyer - arXiv preprint arXiv:2205.11758, 2022"],"snippet":"… This dataset consists of filtered Common Crawl data for 100 languages, with a wide range of data quantities ranging from 0.1 GiB for languages like Xhosa and Scottish Gaelic to over 300 Gib for English. As with XLM-R, we train on CC100 for 1.5M …","url":["https://arxiv.org/pdf/2205.11758"]}
+{"year":"2022","title":"Analyzing the Web: Are Top Websites Lists a Good Choice for Research?","authors":["T Alby, R Jäschke - International Conference on Theory and Practice of …, 2022"],"snippet":"… We present a heuristic-driven alternative based on the Common Crawl host-level web graph while also taking language-… the Common Crawl graph due to 94.9% of hosts in the Common Crawl graph being unknown to the other data sources. Instead …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16802-4_2"]}
+{"year":"2022","title":"ANNA: Enhanced Language Representation for Question Answering","authors":["C Jun, H Jang, M Sim, H Kim, J Choi, K Min, K Bae - arXiv preprint arXiv:2203.14507, 2022"],"snippet":"… of 127,490 wordpieces that are extracted from the English Common Crawl corpus (Raffel et al.… corpora such as a ColossalCleaned version of Common Crawl (C4) corpus (Raffel et al.… for the deletion of documents written in non-English words in …","url":["https://arxiv.org/pdf/2203.14507"]}
+{"year":"2022","title":"Annotation Projection-based Dependency Parser Development for Nepali","authors":["P Rai, S Chatterji - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"Building computational resources and tools for the under-resourced languages is strenuous for any Natural Language Processing (NLP) task. This paper presents the first dependency parser for an under-resourced Indian language, Nepali. A …","url":["https://dl.acm.org/doi/pdf/10.1145/3542696"]}
+{"year":"2022","title":"Answering Binary Causal Questions Using Role-oriented Concept Embedding","authors":["H Kayesh, MS Islam, J Wang - IEEE Transactions on Artificial Intelligence, 2022"],"snippet":"Answering binary causal questions is a challenging task, and it requires rich background knowledge to answer such questions. Extracting useful causal features from the background knowledge base and applying them effectively in a model is a …","url":["https://ieeexplore.ieee.org/abstract/document/9878044/"]}
+{"year":"2022","title":"Answering Consumer Health Questions on the Web","authors":["A Vakili Tahami - 2022"],"snippet":"… In this work, we implement a document filtering technique based on topic-sensitive PageRank that uses a web graph of the hosts in common crawl. We develop a new passage extraction technique that performs query-based contextualized sentence …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18979/VakiliTahami_Amir.pdf?sequence=3&isAllowed=y"]}
+{"year":"2022","title":"APIRO: A Framework for Automated Security Tools API Recommendation","authors":["ZT Sworna, C Islam, MA Babar - arXiv preprint arXiv:2201.07959, 2022"],"snippet":"… Moreover, for augmenting data with the same Aug and same action, we propose to use a wide variety of data sources, ie, thesaurus and embedding (eg, PPDB, GloVe Common Crawl). Hence, a set of 𝛼 number of Data Augmentation …","url":["https://arxiv.org/pdf/2201.07959"]}
+{"year":"2022","title":"AppClassNet: a commercial-grade dataset for application identification research","authors":["C Wang, A Finamore, L Yang, K Fauvel, D Rossi - ACM SIGCOMM Computer …, 2022"],"snippet":"… Similarly, in the NLP field the Common Crawl [2] project gathered several hundreds of billions of text tokens. This is in stark contrast with the networking field where a commonly identified limit to AI deployment is the lack of publicly available …","url":["https://dl.acm.org/doi/abs/10.1145/3561954.3561958"]}
+{"year":"2022","title":"Appendix C: Data Augmentation and Pretraining to Improve Neural Headline Generation in Low-Resource Setting","authors":["M Martinc, S Montariol, L Pivovarova, E Zosa - Cross-Lingual Embeddings for Less …"],"snippet":"We tackle the problem of neural headline generation in a low-resource setting, where only limited amount of data is available to train a model. We compare the ideal high-resource scenario on English with results obtained on a smaller subset of …","url":["http://embeddia.eu/wp-content/uploads/EMBEDDIA-D57-FinalEvaluationReportOnTextGeneration-T54-submitted.pdf#page=54"]}
+{"year":"2022","title":"Application of convolutional deep neural network for human detection in through the wall radar signals","authors":["D Navakauskas, J Skirelis, E Šabanovič, M Kazlauskas… - DAMSS 2022: 13th …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:148962697/148962697.pdf"]}
+{"year":"2022","title":"Application of neural network language models based on distributive semantics for ontological modeling of the domain","authors":["MG Shishaev, VV Dikovitsky, VK Pimeshkov - Journal of Physics: Conference Series, 2022"],"snippet":"… Common Crawl'. The network architecture included 5 layers with a 631-500-350-250-1503 funnel, the ReLU activation function was used, and training was carried out in 15 epochs. The results of testing the resulting model on verification data are shown in …","url":["https://iopscience.iop.org/article/10.1088/1742-6596/2182/1/012033/pdf"]}
+{"year":"2022","title":"Applications of machine learning for COVID-19 misinformation: a systematic review","authors":["AR Sanaullah, A Das, A Das, MA Kabir, K Shu - Social Network Analysis and Mining, 2022"],"snippet":"… (2021) had chosen crawl-300d-2M4 embedding Footnote 4 , a 2 million word vectors which are trained with subword information on Common Crawl (… Footnote 5 which is trained on Common Crawl consisting of 2 million words. Hossain et al. (2020) …","url":["https://link.springer.com/article/10.1007/s13278-022-00921-9"]}
+{"year":"2022","title":"Applying Text Analytics to Insider Risk Analysis: A Case Study on Keyword Generation","authors":["C Gardner, WR Clacyomb - 2022 IEEE International Carnahan Conference on …, 2022"],"snippet":"Recent advancements in text analytics demonstrate significant gains in many natural language processing tasks, taking advantage of newer neural network architectures and transfer learning. In this article, we present findings from a literature review and …","url":["https://ieeexplore.ieee.org/abstract/document/9896598/"]}
+{"year":"2022","title":"Approaching what and how people with mental disorders communicate in social media–Introducing a multi-channel representation","authors":["ME Aragón, AP López-Monroy, LC González… - Neural Computing and …, 2022"],"snippet":"… This model was pre-trained with high-dimensional corpora from Twitter, Common Crawl, and Wikipedia. GloVe presents a lower dimensionality in their word vectors, ranging between 50 and 300 dimensions. GloVe pre-trained with information from …","url":["https://link.springer.com/article/10.1007/s00521-022-07569-8"]}
+{"year":"2022","title":"Arabic abstractive text summarization using RNN-based and transformer-based architectures","authors":["M Bani-Almarjeh, MB Kurdy - Information Processing & Management, 2023"],"snippet":"… To build our dataset, we used Common Crawl to download the archived … Common Crawl are to make it easy to rebuild our dataset by other researchers and to comply with the copyrights of the respective crawled websites. The data are …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322003284"]}
+{"year":"2022","title":"Arabic Fake News Detection: A Fact Checking Based Deep Learning Approach","authors":["F Harrag, MK Djahli - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"Fake news stories can polarize society, particularly during political events. They undermine confidence in the media in general. Current NLP systems are still lacking the ability to properly interpret and classify Arabic fake news. Given the high stakes …","url":["https://dl.acm.org/doi/abs/10.1145/3501401"]}
+{"year":"2022","title":"AraNPCC: The Arabic Newspaper COVID-19 Corpus","authors":["A Al-Thubaity, S Alkhereyf, A Bahanshal - Politics"],"snippet":"This paper introduces a corpus for Arabic newspapers during COVID-19: AraNPCC. The AraNPCC corpus covers 2019 until 2021 via automatically-collected data from 12 Arab countries. It comprises more than 2 billion words and 7.2 million texts …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/OSACT/pdf/2022.osact-1.4.pdf"]}
+{"year":"2022","title":"ArSphere: Arabic word vectors embedded in a polar sphere","authors":["S Rizkallah, AF Atiya, S Shaheen, HED Mahgoub - International Journal of Speech …, 2022"],"snippet":"Word embeddings mean the mapping of words into vectors in an N-dimensional space. ArSphere: is an approach that designs word embeddings for the Arabic language. This approach overcomes one of the shortcomings of word embeddings (for …","url":["https://link.springer.com/article/10.1007/s10772-022-09966-9"]}
+{"year":"2022","title":"Artificial intelligence and the affective labour of understanding: The intimate moderation of a language model","authors":["C Perrotta, N Selwyn, C Ewin - New Media & Society, 2022"],"snippet":"Interest in artificial intelligence (AI) language models has grown considerably following the release of ‘generative pre-trained transformer’ (GPT). Framing AI as an extractive technology, this article details how GPT harnesses human labour and …","url":["https://journals.sagepub.com/doi/abs/10.1177/14614448221075296"]}
+{"year":"2022","title":"Artificial Intelligence, Deepfakes, and Disinformation","authors":["TC HELMUS - 2022"],"snippet":"CAI Content Authenticity Initiative GAN generative adversarial network GPT-3 Generative Pre-Trained Transformer 3 OSINT open-source intelligence technique in American society: increasing disagreement in evaluations of facts and analytical …","url":["https://www.rand.org/content/dam/rand/pubs/perspectives/PEA1000/PEA1043-1/RAND_PEA1043-1.pdf"]}
+{"year":"2022","title":"Artificial Intelligence: A Medium that Hides Its Nature","authors":["A Huxor - Artificial Intelligence and Its Discontents, 2022"],"snippet":"… This technology builds a vast language model based on a corpus of many written texts, drawn from the Internet which themselves previously created by humans, including texts garnered by crawling the web and made available at Common Crawl …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88615-8_6"]}
+{"year":"2022","title":"Artificial Intelligent Context-Aware Machine-Learning Tool to Detect Adverse Drug Events from Social Media Platforms","authors":["D Roosan, AV Law, MR Roosan, Y Li - Journal of Medical Toxicology, 2022"],"snippet":"… We selected FastText embeddings with 300-dimensional vectors and 3 million vocabularies trained with subword information on Common Crawl with 600 Billion tokens to capture the context of our corpus. We used fastText, which has pre-trained …","url":["https://link.springer.com/article/10.1007/s13181-022-00906-2"]}
+{"year":"2022","title":"Artificial Knowing Otherwise","authors":["O Keyes, K Creel - Feminist Philosophy Quarterly, 2022"],"snippet":"… Machine learning’s reliance on free, large-scale resources (some prominent examples include Flickr content for facial and object recognition, Wikipedia for text analysis and image classification, and CommonCrawl for web pages) means that …","url":["https://ojs.lib.uwo.ca/index.php/fpq/article/download/14313/12138"]}
+{"year":"2022","title":"Asking Clarifying Questions: To benefit or to disturb users in Web search?","authors":["J Zou, A Sun, C Long, M Aliannejadi, E Kanoulas - Information Processing & …, 2023"],"snippet":"Modern information-seeking systems are becoming more interactive, mainly through asking Clarifying Questions (CQs) to refine users’ information needs. System-generated CQs may be of different qualities. However, the impact of asking multiple CQs of …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322002771"]}
+{"year":"2022","title":"Assembly Models for SimpleText Task 2: Results from Wuhan University Research Group","authors":["J Huang, J Mao - 2022"],"snippet":"… The pre-trained embedding we choose is trained on Common Crawl, which is from the public domain. There can be pre-trained word embeddings for technology and medical fields, as are the domains covered by the task corpus. Thus, one work …","url":["http://ceur-ws.org/Vol-3180/paper-239.pdf"]}
+{"year":"2022","title":"Assessment of Massively Multilingual Sentiment Classifiers","authors":["K Rajda, Ł Augustyniak, P Gramacki, M Gruza… - arXiv preprint arXiv …, 2022"],"snippet":"… We also included models trained on multilingual corpus like Wikipedia (Wiki) or Common Crawl (CC) as well as models trained with the use of parallel datasets. Selected models differ in size - from LASER with 52M parameters to LaBSE with …","url":["https://arxiv.org/pdf/2204.04937"]}
+{"year":"2022","title":"Assisting Children with Special Needs in Their Daily Interaction with Other People","authors":["M Allouche - 2022"],"snippet":"Children and adults with special needs may find it difficult to recognize danger and threats as well as socially complex situations. They are thus at risk of becoming victims of exploitation and violence. In addition, they may find themselves …","url":["http://azariaa.com/Content/Theses/PhD_MeravA.pdf"]}
+{"year":"2022","title":"ASurvey ON GPT-3","authors":["M Zong, B Krishnamachari - 2022"],"snippet":"This paper provides an introductory survey to GPT-3. We cover some of the historical development behind this technology, some of the key features of GPT-3, and discuss the machine learning model and the datasets used. We survey both academic and …","url":["https://anrg.usc.edu/www/wp-content/uploads/2022/12/A_Survey_On_GPT3.pdf"]}
+{"year":"2022","title":"Attack or Block? Repertoires of Digital Censorship in Autocracies","authors":["L Kawerau, NB Weidmann, A Dainotti - Journal of Information Technology & Politics, 2022"],"snippet":"… When a given host is visited by CommonCrawl multiple times and has the same IP address in two adjacent observations, we assume that the host had the same address on every day between those two observations. We call this period a “stable …","url":["https://www.tandfonline.com/doi/abs/10.1080/19331681.2022.2037118"]}
+{"year":"2022","title":"Attention Fusion: a light yet efficient late fusion mechanism for task adaptation in NLU","authors":["J Cao, CS Prakash, W Hamza, AI Amazon"],"snippet":"Fine-tuning a pre-trained language model using annotated data has become the de-facto standard for adapting general-purpose pretrained models like BERT to downstream tasks. However, given the trend of larger pretrained models, fine-tuning these …","url":["https://assets.amazon.science/99/58/7342d03044d7a4f83324191c4bd3/attention-fusion-a-light-yet-efficient-late-fusion-mechanism-for-task-adaptation-in-nlu.pdf"]}
+{"year":"2022","title":"Attention-Based Bi-LSTM Network for Abusive Language Detection","authors":["KB Nelatoori, HB Kommanti - IETE Journal of Research, 2022"],"snippet":"… These GloVe embeddings are trained on Common Crawl which contains 42 billion tokens and a Twitter corpus with 2 billion tweets. GloVe trained on Twitter contains 25, 50, 100 and 200-dimensional word embeddings with 1.2 million …","url":["https://www.tandfonline.com/doi/abs/10.1080/03772063.2022.2034534"]}
+{"year":"2022","title":"Attention-Based Models for Classifying Small Data Sets Using Community-Engaged Research Protocols: Classification System Development and Validation Pilot …","authors":["BJ Ferrell, SE Raskin, EB Zimmerman, DH Timberline… - JMIR Formative Research, 2022"],"snippet":"Background Community-engaged research (CEnR) is a research approach in which scholars partner with community organizations or individuals with whom they share an interest in the study topic, typically with the goal of supporting that community’s …","url":["https://formative.jmir.org/2022/9/e32460"]}
+{"year":"2022","title":"Attribute Representation in Neural Language Models","authors":["D Yu - 2022"],"snippet":"… Data and preprocessing To train our multilingual model, we use the CommonCrawl dataset from the CoNLL 2017 shared task [96] to obtain monolingual plain text in various languages. To represent words across different languages in a …","url":["https://escholarship.org/content/qt2j78k662/qt2j78k662.pdf"]}
+{"year":"2022","title":"Autoblog 2021: The Importance of Language Models for Spontaneous Lecture Speech","authors":["A Hernandez, P Klumpp, B Das, A Maier, SH Yang - International Conference on Text …, 2022","SH Yang - Text, Speech, and Dialogue: 25th International …, 2022"],"snippet":"… This corpus contains text from news articles, European parliament speeches, and text from Common Crawl [15]. The transcripts from the training set of TED-LIUM 3 [7] based on 2,351 TED talks are used to build a lecture-style LM. While this model is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=qaiJEAAAQBAJ&oi=fnd&pg=PA289&dq=commoncrawl&ots=Nf2wRagpV3&sig=wYalqpKDbKnCbxHtuBrI94UFe2Q","https://link.springer.com/chapter/10.1007/978-3-031-16270-1_24"]}
+{"year":"2022","title":"Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?","authors":["R Dong, Z Qi, L Zhang, J Zhang, J Sun, Z Ge, L Yi… - arXiv preprint arXiv …, 2022"],"snippet":"The success of deep learning heavily relies on large-scale data with comprehensive labels, which is more expensive and time-consuming to fetch in 3D compared to 2D images or natural languages. This promotes the potential of utilizing models …","url":["https://arxiv.org/pdf/2212.08320"]}
+{"year":"2022","title":"Automated Essay Scoring using Transformers","authors":["K Gupta - arXiv preprint arXiv:2210.12809, 2022"],"snippet":"Despite being investigated for over five decades, the task of automated essay scoring continues to draw a lot of attention in the NLP community, in part because of its commercial and educational values as well as the associated research …","url":["https://arxiv.org/pdf/2210.12809"]}
+{"year":"2022","title":"Automated Fake News Detection using cross-checking with reliable sources","authors":["Z Ghadiri, M Ranjbar, F Ghanbarnejad, S Raeisi - arXiv preprint arXiv:2201.00083, 2022"],"snippet":"… We trained this word embedding on Common Crawl and Wikipedia [9]. For two semantically close tweets, their embedding vector should be relatively close. To find the distance between two tweets, we use the cosine between their corresponding vectors. …","url":["https://arxiv.org/pdf/2201.00083"]}
+{"year":"2022","title":"AUTOMATED GENERATION OF MANDARIN EDUCATIONAL MULTIMEDIA CONTENT FROM EXISTING ENGLISH CONTENT","authors":["MJ Israel, A Qin, Y Zhang, J Xin, N Shaghaghi - ICERI2022 Proceedings, 2022"],"snippet":"With the advancement of digital technology, multimedia contents have proliferated in recent years. Large collections of such multimedia content are accrued both in public on the internet and in private enterprise settings. However, the vast majority of …","url":["https://library.iated.org/view/ISRAEL2022AUT"]}
+{"year":"2022","title":"Automated Identification of Toxic Code Reviews: How Far Can We Go?","authors":["J Sarker, AK Turzo, M Dong, A Bosu - arXiv preprint arXiv:2202.13056, 2022"],"snippet":"Toxic conversations during software development interactions may have serious repercussions on a Free and Open Source Software (FOSS) development project. For example, victims of toxic conversations may become afraid to express …","url":["https://arxiv.org/pdf/2202.13056"]}
+{"year":"2022","title":"AUTOMATED LABELING OF MITRE ATT&CK TACTICS AND TECHNIQUES IN MALWARE THREAT REPORTS","authors":["E Domschot - 2022"],"snippet":"… Initially, we used the common crawl GloVe embedding, which was trained over 42 billion tokens, with a 300 dimensional vector space [22]. It was then used as the embedding layer of the BiLSTM model. The results (method GloVe Pretrained) can …","url":["https://search.proquest.com/openview/339b13e8f859e794cefe03c9ef7628d3/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Automated text-level semantic markers of Alzheimer's disease","authors":["C Sanz, F Carrillo, A Slachevsky, G Forno… - Alzheimer's & Dementia …, 2022"],"snippet":"Methods Combining statistical and machine learning analyses of natural speech data, we aimed to discriminate ADD patients from healthy controls (HCs) based on automated measures of domains typically affected in ADD: semantic granularity (coarseness …","url":["https://alz-journals.onlinelibrary.wiley.com/doi/pdf/10.1002/dad2.12276"]}
+{"year":"2022","title":"Automatic and Manual Detection of Generated News: Case Study, Limitations and Challenges","authors":["J Bogaert, A Descampe, MC de Marneffe, FX Standaert - 2022"],"snippet":"In this paper, we study the exploitation of language generation models for disinformation purposes from two viewpoints. Quantitatively, we argue that language models hardly deal with domain adaptation (ie, the ability to generate text on topics …","url":["https://perso.uclouvain.be/fstandae/PUBLIS/277.pdf"]}
+{"year":"2022","title":"Automatic Generation and Detection of Motivational-Interviewing-Style Reflections for Smoking Cessation Therapeutic Conversations Using Transformer-based …","authors":["I Ahmed - 2022"],"snippet":"… The GPT-3 model [9] has 175 billion parameters and is trained on 499GB of text data from multiple datasets: Common Crawl from 2016-2019 [48], WebText, Books1 and Books2 (collection of books and movie script text data) [49], and English-language …","url":["https://www.eecg.utoronto.ca/~jayar/download/ahmed_imtihan_202201_masc_thesis.pdf"]}
+{"year":"2022","title":"Automatic generation of medical reports from chest X-rays in Czech","authors":["L Chaloupský - 2022"],"snippet":"This thesis deals with the problem of automatic generation of medical reports in the Czech language based on the input chest X-ray images using deep neural networks. The first part deals with the analysis of the problem itself including a comparison of …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/176356/120426657.pdf?sequence=1"]}
+{"year":"2022","title":"Automatic Grammar Correction of Commas in Czech Written Texts: Comparative Study","authors":["J Machura, A Frémund, J Švec - International Conference on Text, Speech, and …, 2022","J Švec"],"snippet":"… We used our own pre-trained model from a collection of web data processed in our web mining tool [reference-hidden], Common Crawl data2 and texts collected from the Czech part of Wikipedia. We followed all the training steps, mentioned in [15] …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_10","https://www.researchgate.net/profile/Jakub-Machura-2/publication/363599973_Automatic_Grammar_Correction_of_Commas_in_Czech_Written_Texts_Comparative_Study/links/6347f0bdff870c55ce215a4c/Automatic-Grammar-Correction-of-Commas-in-Czech-Written-Texts-Comparative-Study.pdf"]}
+{"year":"2022","title":"Automatic Pull Request Title Generation","authors":["T Zhang, IC Irsan, F Thung, DG Han, D Lo, L Jiang - arXiv preprint arXiv:2206.10430, 2022"],"snippet":"… Unlike BART, T5 was pre-trained with the Colossal Clean Crawled Corpus (C4) dataset, which consists of 750GB of English text from the public Common Crawl web scrape. T5 was reported to achieve state-of-the-art results on many benchmarks …","url":["https://arxiv.org/pdf/2206.10430"]}
+{"year":"2022","title":"Automatic question answering for multiple stakeholders, the epidemic question answering dataset","authors":["TR Goodwin, D Demner-Fushman, K Lo, LL Wang… - Scientific Data, 2022"],"snippet":"… In the end-to-end collection, we also included 265 Reddit threads as well as a subset of the CommonCrawl News Crawl (CCNC) from … e2e/ccns_trec/ contains 114,645 JSON files, each corresponding to an HTML-parsed website included in the …","url":["https://www.nature.com/articles/s41597-022-01533-w"]}
+{"year":"2022","title":"AUTOMATIC ROMANIAN TEXT GENERATION USING GPT-2","authors":["MC BUZEA, Ș TRĂUȘAN, T REBEDEA"],"snippet":"… from Transformers (BLEURT) – a BLEURT checkpoint was used – a self-contained folder that contained a regression model which was tested on several languages, but should work for the 100+ languages of multilingual C4 (a cleaned version of …","url":["https://www.scientificbulletin.upb.ro/rev_docs_arhiva/rez734_186024.pdf"]}
+{"year":"2022","title":"Automatic Term Extraction with Joint Multilingual Learning","authors":["IN Karaman, I Cicekli, G Ercan - 2022 7th International Conference on Computer …, 2022"],"snippet":"Automatic term extraction using deep learning achieves promising results if sufficient training data exists. Unfortunately, some languages may lack these resources in some domains causing poor performance due to under-fitting. In this study, we …","url":["https://ieeexplore.ieee.org/abstract/document/9919455/"]}
+{"year":"2022","title":"Automatic Text Summarization for Moroccan Arabic Dialect Using an Artificial Intelligence Approach","authors":["I Benelallam - … Intelligence: 7th International Conference, CBI 2022 …"],"snippet":"A major advantage of artificial intelligence is its ability to automatically perform tasks at a human-like level quickly; this is needed in many fields, and more particularly in Automatic Text Summarization (ATS). Several advances related to this technique …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=mZxvEAAAQBAJ&oi=fnd&pg=PA158&dq=commoncrawl&ots=R3bP_X-osy&sig=StHLey4LgAHWwHnofHZYygV5YzA"]}
+{"year":"2022","title":"Automatic text summarization of konkani texts using pre-trained word embeddings and deep learning.","authors":["J D'Silva, U Sharma - International Journal of Electrical & Computer …, 2022"],"snippet":"… The models are trained on documents from Common Crawl and Wikipedia to obtain embeddings for words in the languages offered [12], [13]. With Konkani, the number of Konkani language articles is significantly low on Wikipedia compared to …","url":["http://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=20888708&AN=154204023&h=YgeWf2sTl1O%2FMKtu7OeHz%2FHcc2De9w9RwaYA14TSEkzxauPv0vrRqD%2Bdn4LVWiwHi7XNZke8S5Wuv%2BL1wGg8hQ%3D%3D&crl=c"]}
+{"year":"2022","title":"Automating Feedback to Improve Teachers' Effective Use of Instructional Discourse in K-12 Mathematics Classrooms","authors":["A Suresh - 2022"],"snippet":"… In our model, we use the vectors trained on Common Crawl with 840 billion tokens and 300 dimensions. For a given sentence, we identify the GloVe representation for each word in the sentence and compute a mean vector. …","url":["https://search.proquest.com/openview/15e25cc3c1547a2e1390d398d1ea42fd/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Automating Idea Unit Segmentation and Alignment for Assessing Reading Comprehension via Summary Protocol Analysis","authors":["M Gecchele, H Yamada, T Tokunaga, Y Sawaki…"],"snippet":"In this paper, we approach summary evaluation from an applied linguistics (AL) point of view. We provide computational tools to AL researchers to simplify the process of Idea Unit (IU) segmentation. The IU is a segmentation unit that can …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.498.pdf"]}
+{"year":"2022","title":"Autonomous schema markups based on intelligent computing for search engine optimization","authors":["BUD Abbasi, I Fatima, H Mukhtar, S Khan, A Alhumam… - PeerJ Computer Science, 2022"],"snippet":"With advances in artificial intelligence and semantic technology, search engines are integrating semantics to address complex search queries to improve the results. This requires identification of well-known concepts or entities and their relationship from …","url":["https://peerj.com/articles/cs-1163/"]}
+{"year":"2022","title":"Balancing between holistic and cumulative sentiment classification","authors":["P Agathangelou, I Katakis - Online Social Networks and Media, 2022"],"snippet":"Sentiment analysis is a fast-accelerating discipline that develops algorithms for knowledge discovery from opinionated content. The challenges however, when it comes to analyzing user reviews are plenty. Bad-quality, informal use of language …","url":["https://www.sciencedirect.com/science/article/pii/S2468696422000039"]}
+{"year":"2022","title":"Balancing novelty and appropriateness leads to creative associations in children","authors":["C Rastelli, A Greco, N De Pisapia, C Finocchiaro - 2022"],"snippet":"Creative cognition is conceived as the process whereby something novel and appropriate is generated. However, the contribution of novelty and appropriateness to creativity is far from being understood, especially during developmental age. Here …","url":["https://psyarxiv.com/k5pz3/download?format=pdf"]}
+{"year":"2022","title":"BanglaNLG: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla","authors":["A Bhattacharjee, T Hasan, WU Ahmad, R Shahriyar - arXiv preprint arXiv:2205.11081, 2022"],"snippet":"This work presents BanglaNLG, a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language in the web domain. We aggregate three challenging conditional text …","url":["https://arxiv.org/pdf/2205.11081"]}
+{"year":"2022","title":"Based on billions of words on the internet,< scp> people</scp>=< scp> men</scp","authors":["AH Bailey, A Williams, A Cimpian"],"snippet":"Recent advances have made it possible to precisely measure the extent to which any two words are used in similar contexts. In turn, this measure of similarity in linguistic context also captures the extent to which the concepts being denoted are …","url":["https://ouci.dntb.gov.ua/en/works/733X5j07/"]}
+{"year":"2022","title":"Being Polite: Modeling Politeness Variation in a Personalized Dialog Agent","authors":["M Firdaus, A Shandilya, A Ekbal, P Bhattacharyya - IEEE Transactions on …, 2022"],"snippet":"… The word embedding dimension is set as 300 for which we use FastText Embeddings [52] pretrained on the common crawl. We apply 0.5 dropout rate [53] to the layer before softmax. All the models are trained on a single NVIDIA 1080Ti GPU. …","url":["https://ieeexplore.ieee.org/abstract/document/9801557/"]}
+{"year":"2022","title":"Benchmarking Library Recognition in Tweets","authors":["T Zhang, DP Chandrasekaran, F Thung, D Lo - 2022"],"snippet":"… News dataset); OpenWebText [2] (an open-source recreation of the WebText corpus), and Stories [40] (a subset of CommonCrawl data that … Compared to BERT, XLNet also involved more pre-training data, such as Common Crawl [1]. XLNet …","url":["https://happygirlzt.com/files/icpc22.pdf"]}
+{"year":"2022","title":"Benchmarking Transformers-based models on French Spoken Language Understanding tasks","authors":["O Cattan, S Ghannay, C Servan, S Rosset - INTERSPEECH 2022, 2022"],"snippet":"… Most models are pre-trained on the content of either Wikipedia, the web pages gathered by Common Crawl (CC) or a combination of diverse corpora. This represents a few gigabytes to several hundred or even several terabytes of text. The …","url":["https://hal.archives-ouvertes.fr/hal-03715340/document"]}
+{"year":"2022","title":"Benefits from Variational Regularization in Language Models","authors":["C Ferner, S Wegenkittl - Machine Learning and Knowledge Extraction, 2022"],"snippet":"… WMT19 contains data from news commentaries, Wiki titles, Europarl, ParaCrawl, and Common Crawl corpora. The data are tokenized using … Both BERT and MiniBERT were trained on a much larger collection of datasets (Wikipedia …","url":["https://www.mdpi.com/2504-4990/4/2/25/pdf?version=1654773213"]}
+{"year":"2022","title":"Bengali POS Tagging Using Bi-LSTM with Word Embedding and Character-Level Embedding","authors":["K Bose, K Sarkar - COMSYS 2021"],"snippet":"Part-of-speech tagging (POS) is an important and very fundamental process in natural language processing (NLP). POS tagging is required as a preprocessing task in many types of linguistic research such as named entity recognition (NER) …","url":["https://link.springer.com/content/pdf/10.1007/978-981-19-0105-8.pdf#page=563"]}
+{"year":"2022","title":"Bernice: A Multilingual Pre-trained Encoder for Twitter","authors":["A DeLucia, S Wu, A Mueller, C Aguirre, M Dredze…"],"snippet":"… XLM-T and TwHIN-BERT* models use the XLM-R tokenizer, which was trained on out-of-domain CommonCrawl data and has the same vocabulary size as Bernice (250K tokens), but covers 100 languages versus 66.While trained on tweets, BERTweet is …","url":["https://www.cs.jhu.edu/~mdredze/publications/2022_emnlp_bernice.pdf"]}
+{"year":"2022","title":"BERT based Multiple Parallel Co-attention Model for Visual Question Answering","authors":["M Dias, H Aloj, N Ninan, D Koshti - 2022 6th International Conference on Intelligent …, 2022"],"snippet":"Humans can easily interpret visual and textual content whereas for a machine this is a challenging task. Visual question answering is a well-known problem in the field of computer vision and NLP where an image and a question related to the image are …","url":["https://ieeexplore.ieee.org/abstract/document/9788253/"]}
+{"year":"2022","title":"Bertifying sinhala-a comprehensive analysis of pre-trained language models for sinhala text classification","authors":["V Dhananjaya, P Demotte, S Ranathunga, S Jayasena - Proceedings of the 13th …, 2022"],"snippet":"This research provides the first comprehensive analysis of the performance of pre-trained language models for Sinhala text classification. We test on a set of different Sinhala text classification tasks and our analysis shows that out of the pre-trained …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.803.pdf"]}
+{"year":"2022","title":"BERTuit: Understanding Spanish language in Twitter through a native transformer","authors":["J Huertas-Tato, A Martin, D Camacho - arXiv preprint arXiv:2204.03465, 2022"],"snippet":"The appearance of complex attention-based language models such as BERT, Roberta or GPT-3 has allowed to address highly complex tasks in a plethora of scenarios. However, when applied to specific domains, these models encounter …","url":["https://arxiv.org/pdf/2204.03465"]}
+{"year":"2022","title":"Beyond Counting Datasets: A Survey of Multilingual Dataset Construction and Necessary Resources","authors":["J Hu, E Choi"],"snippet":"While the NLP community is generally aware of resource disparities among languages, we lack research that quantifies the extent and types of such disparity. Prior surveys estimating the availability of resources based on the number of …","url":["https://akariasai.github.io/files/multilingual_datasets_analysis_emnlp_findings_2022.pdf"]}
+{"year":"2022","title":"Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning","authors":["B Patra, S Singhal, S Huang, Z Chi, L Dong, F Wei… - arXiv preprint arXiv …, 2022"],"snippet":"… 2020) which contains texts in 100 languages collected from Common Crawl. As mentioned in (§3.1), we explore the utility of the CCMatrix and the … Furthermore, the raw data was compiled from static Common Crawl snapshots from January …","url":["https://arxiv.org/pdf/2210.14867"]}
+{"year":"2022","title":"Bilingual attention based neural machine translation","authors":["L Kang, S He, M Wang, F Long, J Su - Applied Intelligence, 2022"],"snippet":"… Our contrast models mainly include (1) the winning system in WMT2014 [3], a phrase-based system of which language models were trained on the Common Crawl corpus; (2) GNMT [16] that is the most competitive RNN-based NMT model to …","url":["https://link.springer.com/article/10.1007/s10489-022-03563-8"]}
+{"year":"2022","title":"Bilingual Tabular Inference: A Case Study on Indic Languages","authors":["C Agarwal, V Gupta, A Kunchukuttan, M Shrivastava"],"snippet":"Existing research on Tabular Natural Language Inference (TNLI) exclusively examines the task in a monolingual setting where the tabular premise and hypothesis are in the same language. However, due to the uneven distribution of …","url":["https://vgupta123.github.io/docs/NAACL2022.pdf"]}
+{"year":"2022","title":"Biomedical Semantic Textual Similarity: Evaluation of Sentence Representations Enhanced with Principal Component Reduction and Word Frequency Weighting","authors":["K Kantor, M Morzy - International Conference on Artificial Intelligence in …, 2022"],"snippet":"… We examine 50-dimension and 300-dimension GloVe models built on Wikipedia corpus and 300-dimension models trained on the Common Crawl. We choose the BERT model [7] trained on BookCorpus and English Wikipedia for neural-based …","url":["https://link.springer.com/chapter/10.1007/978-3-031-09342-5_39"]}
+{"year":"2022","title":"Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages","authors":["K Heffernan, O Çelebi, H Schwenk - arXiv preprint arXiv:2205.12654, 2022"],"snippet":"… Our monolingual data comes mostly from Common Crawl and other public sources like ParaCrawl5, and some additional targeted … Our main source of monolingual data was Common Crawl, complemented and targeted crawling (see …","url":["https://arxiv.org/pdf/2205.12654"]}
+{"year":"2022","title":"BJTU-WeChat's Systems for the WMT22 Chat Translation Task","authors":["Y Liang, F Meng, J Xu, Y Chen, J Zhou - arXiv preprint arXiv:2211.15009, 2022"],"snippet":"… For monolingual data, we use the News Crawl, Common Crawl, and Extended Common Crawl. For synthetic data generation, we back-translate all the target monolingual data and forward-translate the source monolingual data. For the in-domain …","url":["https://arxiv.org/pdf/2211.15009"]}
+{"year":"2022","title":"BLOOM: A 176B-Parameter Open-Access Multilingual Language Model","authors":["TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow… - arXiv preprint arXiv …, 2022"],"snippet":"… The latter required the development of new tools to extract text from the HTML in the Common Crawl WARC files, which we made available on the main data preparation repository.We were able to find and extract usable text data from all …","url":["https://arxiv.org/pdf/2211.05100"]}
+{"year":"2022","title":"Boosting named entity recognition in domain-specific and low-resource settings","authors":["S Najem-Meyer - 2022"],"snippet":"Recent researches in natural language processing have leveraged attention-based models to produce state-of-the-art results in a wide variety of tasks. Using transfer learning, generic models like BERT can be fine-tuned for domain-specific tasks …","url":["https://infoscience.epfl.ch/record/291236/files/2021SemProj___Boosting_NER%20%281%29.pdf"]}
+{"year":"2022","title":"Bootstrapping Icelandic Knowledge Graph Data","authors":["SR Friðriksdóttir, H Einarsson - 2022"],"snippet":"… The model is trained on several sources of bitext data, including ccMatrix [13], ccAligned [3] and OPUS [15], as well as monolingual data from Common Crawl 2. The model uses a modified transformer architecture which reaches a BLEU-score of …","url":["https://scholar.archive.org/work/rx2eruubtrfubafg3hnrvrz65q/access/wayback/https://s3.nl-ams.scw.cloud/pstorage-amster-45168546/36407967/FririksdttirEinarsson2022BootstrappingIcelandicKnowledgeGraphData.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=SCW90ENHXE6G7FVJV73C/20220729/nl-ams/s3/aws4_request&X-Amz-Date=20220729T090312Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=1a3d652c1534a09b587552fc159ec377ec6b493140a3c488e49368e28e36bb77"]}
+{"year":"2022","title":"Bridging Cross-Lingual Gaps During Leveraging the Multilingual Sequence-to-Sequence Pretraining for Text Generation","authors":["C Zan, L Ding, L Shen, Y Cao, W Liu, D Tao - arXiv preprint arXiv:2204.07834, 2022"],"snippet":"For multilingual sequence-to-sequence pretrained language models (multilingual Seq2Seq PLMs), eg mBART, the self-supervised pretraining task is trained on a wide range of monolingual languages, eg 25 languages from commoncrawl, while …","url":["https://arxiv.org/pdf/2204.07834"]}
+{"year":"2022","title":"Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering Architecture","authors":["K Pearce, S Alghowinem, C Breazeal - arXiv preprint arXiv:2212.07542, 2022"],"snippet":"As artificial intelligence (AI) becomes a prominent part of modern life, AI literacy is becoming important for all citizens, not just those in technology careers. Previous research in AI education materials has largely focused on the introduction of …","url":["https://arxiv.org/pdf/2212.07542"]}
+{"year":"2022","title":"Building a Closed-Domain Question Answering System for a Low-Resource Language","authors":["P Tran, D Nguyen, HA Tran, T Nguyen, T Tran - Transactions on Asian and Low …, 2022"],"snippet":"… The authors announced two models including XLM-Rbase with 250 million parameters and XLM-Rlarge with 560 million parameters trained over 2.5 terabytes of data in 100 languages (including Vietnamese) from Common Crawl. XLM-R …","url":["https://dl.acm.org/doi/pdf/10.1145/3566123"]}
+{"year":"2022","title":"Building a comprehensive NER model for Satellite Domain","authors":["P Maurya, O Jafari, B Thatte, C Ingram, P Nagarkar - SN Computer Science, 2022"],"snippet":"… A model trained on the OntoNotes 5 and GloVe Common Crawl datasets. All of these models can recognize types of entities such as PERSON, NORP, FAC, ORG, GPE, LOC, PRODUCT, EVENT, WORK_OF_ART, LAW, LANGUAGE, DATE, TIME …","url":["https://link.springer.com/article/10.1007/s42979-022-01085-1"]}
+{"year":"2022","title":"Building a Connected Web Observatory","authors":["T Tiropanis, X Wang, R Tinati, W Hall"],"snippet":"… For the SUWO, we are harvesting a variety of Web feeds, which include real-time streams from social networking and user-generated content sites (Twitter, Facebook, YouTube), Web-crawled datasets using existing resources such as the ’CommonCrawl’1 …","url":["https://www.academia.edu/download/78199864/web-obs-arch-bwow14.pdf"]}
+{"year":"2022","title":"Building a Multilingual Taxonomy of Olfactory Terms with Timestamps","authors":["S Menini, T Paccosi, SS Tekiroglu, S Tonelli - To"],"snippet":"Olfactory references play a crucial role in our memory and, more generally, in our experiences, since researchers have shown that smell is the sense that is most directly connected with emotions. Nevertheless, only few works in NLP have tried to …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.429.pdf"]}
+{"year":"2022","title":"Building AI Enabled Note-taking Interfaces for Patient Encounters","authors":["J Wang - 2022"],"snippet":"Current clinical note-taking approaches cannot capture the entirety of information available from patient encounters and detract from patient-clinician interactions. To address those issues we investigate the feasibility and suitability of using artificial …","url":["https://tspace.library.utoronto.ca/bitstream/1807/123369/1/Wang_Jixuan__202206_PhD_thesis.pdf"]}
+{"year":"2022","title":"Building better machine learning models for rhetorical analyses: The use of rhetorical feature sets for training artificial neural network models","authors":["ZP Majdik, J Wynn - Technical Communication Quarterly, 2022"],"snippet":"In this paper, we investigate two approaches to building artificial neural network models to compare their effectiveness for accurately classifying rhetorical structures across multiple (non-binary) classes in small textual datasets. We find that the most …","url":["https://www.tandfonline.com/doi/abs/10.1080/10572252.2022.2077452"]}
+{"year":"2022","title":"Building Comparable Corpora for Assessing Multi-Word Term Alignment","authors":["O Adjali, E Morin, P Zweigenbaum - Proceedings of the 13th Language Resources …, 2022"],"snippet":"Recent work has demonstrated the importance of dealing with Multi-Word Terms (MWTs) in several Natural Language Processing applications. In particular, MWTs pose serious challenges for alignment and machine translation systems because of their …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.332.pdf"]}
+{"year":"2022","title":"Building Korean NER models for a manually annotated corpus from clinical notes using cross-lingual transfer learning","authors":["J Li, J Park, X Hu, J Wang, RW Park, H Xu"],"snippet":"… text dataset, BERT-MULTILINGUALBASE was a multilingual BERT model that was pre-trained on 104 languages with the largest Wikipedias dataset, and XLM-ROBERTABASE was a multilingual language model that was pre-trained on 100 languages with 2TB …","url":["https://www.ohdsi.org/wp-content/uploads/2022/10/96-Jianfu-Li_KoreanClinicalNotesNER_2022symposium-Jianfu-Li.pdf"]}
+{"year":"2022","title":"Building Machine Translation System for Software Product Descriptions Using Domain-specific Sub-corpora Extraction","authors":["P Lohar, S Madden, E O'Connor, M Popović… - Proceedings of the 15th …, 2022"],"snippet":"Building Machine Translation systems for a specific domain requires a sufficiently large and good quality parallel corpus in that domain. However, this is a bit challenging task due to the lack of parallel data in many domains such as economics …","url":["https://aclanthology.org/2022.amta-research.1.pdf"]}
+{"year":"2022","title":"Building Sentiment Lexicons for Mainland Scandinavian Languages Using Machine Translation and Sentence Embeddings","authors":["P Liu, C Marco, JA Gulla"],"snippet":"This paper presents a simple but effective method to build sentiment lexicons for the three Mainland Scandinavian languages: Danish, Norwegian and Swedish. This method benefits from the English Sentiwordnet and a thesaurus in one of the target …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.301.pdf"]}
+{"year":"2022","title":"Building Siamese Attention-Augmented Recurrent Convolutional Neural Networks for Document Similarity Scoring","authors":["S Han, L Shi, R Richie, FR Tsui - Information Sciences, 2022"],"snippet":"Automatically measuring document similarity is imperative in natural language processing, with applications ranging from recommendation to duplicate document detection. State-of-the-art approach in document similarity commonly involves deep …","url":["https://www.sciencedirect.com/science/article/pii/S0020025522011537"]}
+{"year":"2022","title":"Business Document Information Extraction: Towards Practical Benchmarks","authors":["M Skalický, Š Šimsa, M Uřičář, M Šulc - arXiv preprint arXiv:2206.11229, 2022"],"snippet":"… [93] was not published, while pre-training on it was crucial for the proposed method, and the C4 dataset [64] is shared in the form of code that extracts it directly from Common Crawl. Publicly available datasets for KI(L)E from business …","url":["https://arxiv.org/pdf/2206.11229"]}
+{"year":"2022","title":"C-OSINT: COVID-19 Open Source artificial INTelligence framework","authors":["L Ranaldi, A Nourbakhsh, F Fallucchid, FM Zanzotto - 2022"],"snippet":"With the emergence of COVID-19 disease worldwide, a market of the products related to this disease formed across the Internet. By the time these goods were in short supply, many uncontrolled Dark Web Marketplaces (DWM) were active in …","url":["http://ceur-ws.org/Vol-3260/paper16.pdf"]}
+{"year":"2022","title":"Can Cross-Domain Term Extraction Benefit from Cross-lingual Transfer?","authors":["HTH Tran, M Martinc, A Doucet, S Pollak - International Conference on Discovery …, 2022"],"snippet":"Automatic term extraction (ATE) is a natural language processing task that eases the effort of manually identifying terms from domain-specific corpora by providing a list of candidate terms. In this paper, we experiment with XLM-RoBERTa to evaluate the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-18840-4_26"]}
+{"year":"2022","title":"Can Foundation Models Help Us Achieve Perfect Secrecy?","authors":["S Arora, C Ré - arXiv preprint arXiv:2205.13722, 2022"],"snippet":"… 4A particular challenge was obtaining an FM for Reddit, since most FMs are trained on generic Common Crawl — we thus use Grover FMs, which are pretrained only on news articles and find the performance of Grover models directly match or …","url":["https://arxiv.org/pdf/2205.13722"]}
+{"year":"2022","title":"Can linguistic features extracted from geo-referenced tweets help building function classification in remote sensing?","authors":["M Häberle, EJ Hoffmann, XX Zhu - ISPRS Journal of Photogrammetry and Remote …, 2022"],"snippet":"… To add more heterogeneous language, they additionally utilized CommonCrawl 13 to train the word embedding using fastText, and words were left in upper and lower case to add some semantics and context to words (cf. Section 3.4). For our …","url":["https://www.sciencedirect.com/science/article/pii/S0924271622001058"]}
+{"year":"2022","title":"Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?","authors":["P Schramowski, C Tauchmann, K Kersting - arXiv preprint arXiv:2202.06675, 2022"],"snippet":"… The most recent and successful models, such as GPT-3 [5], CLIP [36], DALL-E [38] and other similar models, are trained on data scraped from the web, eg using CommonCrawl. The information they acquire from this data is largely uncontrolled …","url":["https://arxiv.org/pdf/2202.06675"]}
+{"year":"2022","title":"Capturing Failures of Large Language Models via Human Cognitive Biases","authors":["E Jones, J Steinhardt - arXiv preprint arXiv:2202.12299, 2022"],"snippet":"Large language models generate complex, open-ended outputs: instead of outputting a single class, they can write summaries, generate dialogue, and produce working code. In order to study the reliability of these open-ended systems, we must …","url":["https://arxiv.org/pdf/2202.12299"]}
+{"year":"2022","title":"Catching a Phish: Frontiers of Deep Learning-Based Anticipating Detection Engines","authors":["H Salah, H Zuhair - International Conference of Reliable Information and …, 2022"],"snippet":"In recent years, cyber-security gains high attention in the light of ethical hacking and social engineering attacks like phishing that riskily overshadow the development of social networking, e commerce, and information technology. Thus, mitigation of such …","url":["https://link.springer.com/chapter/10.1007/978-3-030-98741-1_40"]}
+{"year":"2022","title":"CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks","authors":["X He, Q Xu, Y Zeng, L Lyu, F Wu, J Li, R Jia - arXiv preprint arXiv:2209.08773, 2022"],"snippet":"… Since the training data of the victim model is unknown to the malicious users, we randomly select 5M sentences from common crawl data as the benign corpus. Then we obtain the word distribution for the watermarked and benign corpora, respectively …","url":["https://arxiv.org/pdf/2209.08773"]}
+{"year":"2022","title":"CausalDialogue: Modeling Utterance-level Causality in Conversations","authors":["YL Tuan, A Albalak, W Xu, M Saxon, C Pryor, L Getoor… - arXiv preprint arXiv …, 2022"],"snippet":"Despite their widespread adoption, neural conversation models have yet to exhibit natural chat capabilities with humans. In this research, we examine user utterances as causes and generated responses as effects, recognizing that changes in a cause …","url":["https://arxiv.org/pdf/2212.10515"]}
+{"year":"2022","title":"Cedille: A large autoregressive French language model","authors":["M Müller, F Laurent - arXiv preprint arXiv:2202.03371, 2022"],"snippet":"… Experiments conducted on GPT-3 (which has been trained on 570GB of text data from Common Crawl) show that the model may generate toxic sentences even when prompted with non-toxic text [11]. Although applying filtering of training data using …","url":["https://arxiv.org/pdf/2202.03371"]}
+{"year":"2022","title":"Challenges and limits of an open source approach to Artificial Intelligence","authors":["A THEBEN, L GUNDERSON, L LÓPEZ-FORÉS…"],"snippet":"… It takes the GPT model to a whole new level as it is trained on a massive number of parameters (ie 175 billions, which is over 10x the size of its predecessor) on an open source dataset called 'Common Crawl,' and other texts from OpenAI such as …","url":["https://www.staten-generaal.nl/eu/documenteu/pe_662908_challenges_and_limits_of/f=/vlkvn20v47an.pdf"]}
+{"year":"2022","title":"Challenges in Measuring Bias via Open-Ended Language Generation","authors":["AF Akyürek, MY Kocyigit, S Paik, D Wijaya - arXiv preprint arXiv:2205.11601, 2022"],"snippet":"Researchers have devised numerous ways to quantify social biases vested in pretrained language models. As some language models are capable of generating coherent completions given a set of textual prompts, several prompting datasets …","url":["https://arxiv.org/pdf/2205.11601"]}
+{"year":"2022","title":"Changing Language Ideological Concepts in the Human-Machine Era. Questions, Themes and Topics","authors":["D Dippold, I Erdocia, T Fester-Seeger, S Höhn…"],"snippet":"It introduces general thoughts on language ideological reformulations in the age of digital technologies as well as exemplary empirical studies that display language ideological changes, conducted by individual members of the Working Group. In this …","url":["https://www.researchgate.net/profile/Britta-Schneider/publication/365838026_Changing_Language_Ideological_Concepts_in_the_Human-Machine_Era_Questions_Themes_and_Topics/links/63860e357b0e356feb974905/Changing-Language-Ideological-Concepts-in-the-Human-Machine-Era-Questions-Themes-and-Topics.pdf"]}
+{"year":"2022","title":"Changing the Narrative Perspective: A New Language Processing Task and Machine Learning Approaches","authors":["M Chen - 2022"],"snippet":"In this dissertation I introduce the novel text processing task of changing the narrative perspective, where characters in a story are assigned a point of view that is di erent from the one originally used by the writer. The resulting shift in the narrative …","url":["https://etd.ohiolink.edu/apexprod/rws_etd/send_file/send?accession=ohiou1647655979201374&disposition=inline"]}
+{"year":"2022","title":"ChapterBreak: A Challenge Dataset for Long-Range Language Models","authors":["S Sun, K Thai, M Iyyer - arXiv preprint arXiv:2204.10878, 2022"],"snippet":"While numerous architectures for long-range language models (LRLMs) have recently been proposed, a meaningful evaluation of their discourse-level language understanding capabilities has not yet followed. To this end, we introduce …","url":["https://arxiv.org/pdf/2204.10878"]}
+{"year":"2022","title":"Characterization and Prediction of Mobile Tasks","authors":["Y Tian, K Zhou, D Pelleg - ACM Transactions on Information Systems (TOIS), 2022"],"snippet":"Mobile devices have become an increasingly ubiquitous part of our everyday life. We use mobile services to perform a broad range of tasks (eg, booking travel or conducting remote office work), leading to often lengthy interactions with several …","url":["https://dl.acm.org/doi/abs/10.1145/3522711"]}
+{"year":"2022","title":"Characterizing accident narratives with word embeddings: Improving accuracy, richness, and generalizability","authors":["DM Goldberg - Journal of Safety Research, 2021"],"snippet":"Introduction: Ensuring occupational health and safety is an enormous concern for organizations, as accidents not only harm workers but also result in financial losses. Analysis of accident data has the potential to reveal insights that may improve …","url":["https://www.sciencedirect.com/science/article/pii/S0022437521001754"]}
+{"year":"2022","title":"Characterizing and Resolving Degeneracies in Neural Autoregressive Text Generation","authors":["I Kulikov - 2022"],"snippet":"… We use the subset of WMT’19 training set consisting of news commentary v12 and common crawl resulting in slightly more than 1M and 2M training sentence pairs for Ru→En and De↔En pairs, respectively. We ne-tuned single model checkpoints …","url":["https://search.proquest.com/openview/b0268b79afd971636daec6ad90c0ec2c/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering","authors":["M Luo, K Hashimoto, S Yavuz, Z Liu, C Baral, Y Zhou - arXiv preprint arXiv …, 2022"],"snippet":"While both extractive and generative readers have been successfully applied to the Question Answering (QA) task, little attention has been paid toward the systematic comparison of them. Characterizing the strengths and weaknesses of the two …","url":["https://arxiv.org/pdf/2203.07522"]}
+{"year":"2022","title":"City of Disguise: A Query Obfuscation Game on the ClueWeb","authors":["M Fröbe, NL Libera, M Hagen"],"snippet":"We present City of Disguise, a retrieval game that tests how well searchers are able to reformulate some sensitive query in a ‘Taboo’-style setup but still retrieve good results. Given one of 200 sensitive information needs and a relevant example …","url":["https://webis.de/downloads/publications/papers/froebe_2022b.pdf"]}
+{"year":"2022","title":"Classification of Construction Accident Court Cases Via Natural Language Processing in Hong Kong","authors":["RYM Li, HCY Li, B Tang, WC Au - Current State of Art in Artificial Intelligence and …, 2022"],"snippet":"… The fastText system has a trained English language vector model derived from Wikipedia, Common Crawl and other sources. Every word is stored along with several different tokens, and the morphology and word representations are replaced …","url":["https://link.springer.com/chapter/10.1007/978-981-19-0737-1_5"]}
+{"year":"2022","title":"Classification of German Jungian Extraversion and Introversion Texts with Assessment of Changes during the COVID-19 Pandemic","authors":["D Johannßen, C Biemann, D Scheffer"],"snippet":"The corona pandemic and countermeasures such as social distancing and lockdowns have confronted individuals with new challenges for their mental health and well-being. It can be assumed that the Jungian psychology types of extraverts …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2022-johannssen-biemann-scheffer-rapid4.pdf"]}
+{"year":"2022","title":"Classification of Indian Media Titles using Deep Learning Techniques","authors":["S Kumar, DD Rajesh, S Pranesh, VNH Kollipara… - International Journal of …, 2022"],"snippet":"Automatic speech recognition is being used everywhere these days. An essential part of this is language identification. Our goal here is to identify the language of the media title, such as song names and movie titles, to help in speech recognition. The …","url":["https://www.sciencedirect.com/science/article/pii/S2666307422000109"]}
+{"year":"2022","title":"Classification of Layout vs Relational Tables on the Web: Machine Learning with Rendered Pages","authors":["W Haider, Y Yesilada - ACM Transactions on the Web (TWEB), 2022"],"snippet":"Table mining on the web is an open problem, and none of the previously proposed techniques provides a complete solution. Most research focuses on the structure of the HTML document, but because of the nature and structure of the web, it is still a …","url":["https://dl.acm.org/doi/abs/10.1145/3555349"]}
+{"year":"2022","title":"Classifying and labeling the relationships between cities with high levels of co-occurrence on the English Wikipedia","authors":["D Rijen - 2022"],"snippet":"This study delves into three different approaches of document classification in order to successfully classify the type of relationship between European cities: ”LDA Topic modeling, Word embedding classification and Word frequency representation”. The …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/42413/THESIS__CITYNET____APPLIED_DATA_SCIENCE_FINAL_V3.pdf?sequence=1"]}
+{"year":"2022","title":"Classifying Documents by Viewpoint Using Word2Vec and Support Vector Machines","authors":["J Harwell, Y Li - International Conference on Applications of Natural …, 2022"],"snippet":"Ensuring viewpoint diversity in mass media is a historical challenge and recent political events, and the ever-increased use of the Internet, have made it an increasingly critical and contentious issue. This research explores the relationship …","url":["https://link.springer.com/chapter/10.1007/978-3-031-08473-7_13"]}
+{"year":"2022","title":"Classifying multi-level product categories using dynamic masking and transformer models","authors":["O Ozyegen, H Jahanshahi, M Cevik, B Bulut, D Yigit… - Journal of Data, Information …, 2022"],"snippet":"In an online shopping platform, a detailed categorization of the products greatly enhances user navigation. Online retailers also benefit from well-defined product categories as various sales and marketing operations such as special discounts and …","url":["https://link.springer.com/article/10.1007/s42488-022-00066-6"]}
+{"year":"2022","title":"ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization","authors":["J Wang, F Meng, Z Lu, D Zheng, Z Li, J Qu, J Zhou - arXiv preprint arXiv:2202.05599, 2022"],"snippet":"We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents. It consists of 67k+ dialogue documents from two subsets (ie, SAMSum and MediaSum) and 112k+ annotated summaries in different …","url":["https://arxiv.org/pdf/2202.05599"]}
+{"year":"2022","title":"CLSE: Corpus of Linguistically Significant Entities","authors":["A Chuklin, J Zhao, M Kale - arXiv preprint arXiv:2211.02423, 2022"],"snippet":"One of the biggest challenges of natural language generation (NLG) is the proper handling of named entities. Named entities are a common source of grammar mistakes such as wrong prepositions, wrong article handling, or incorrect entity …","url":["https://arxiv.org/pdf/2211.02423"]}
+{"year":"2022","title":"ClueWeb22: 10 Billion Web Documents with Rich Information","authors":["A Overwijk, C Xiong, J Callan - Proceedings of the 45th International ACM SIGIR …, 2022"],"snippet":"… One approach is to sift CommonCrawl data, eg, the C4 dataset used to pretrain T5 [10], which provides sufficient quantity, but the quality quickly becomes a concern. For example, the cleaned CommonCrawl reflects a quite weird distribution of the …","url":["https://dl.acm.org/doi/abs/10.1145/3477495.3536321"]}
+{"year":"2022","title":"CM3: A Causal Masked Multimodal Model of the Internet","authors":["A Aghajanyan, B Huang, C Ross, V Karpukhin, H Xu… - arXiv preprint arXiv …, 2022"],"snippet":"… on close to a Terabyte of multi-modal simplified HTML data from the common crawl. • We present the causally masked objective, a hybrid of … all of Common Crawl and instead opt into using a subset of the Common Crawl News (CC-NEWS) …","url":["https://arxiv.org/pdf/2201.07520"]}
+{"year":"2022","title":"CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learning","authors":["X Liu, Z Zhang, Y Wang, Y Lan, C Shen - arXiv preprint arXiv:2212.10341, 2022"],"snippet":"… (2019a), in which HWTs are collected from RealNews, a large corpus of news articles from Common Crawl, and MGTs are generated by Grover-Mega, a transformer-based news generator with parameters sized 1.5B. …","url":["https://arxiv.org/pdf/2212.10341"]}
+{"year":"2022","title":"Cognitive linguistics meets computational linguistics: Construction grammar, dialectology, and linguistic diversity","authors":["J Dunn - Data Analytics in Cognitive Linguistics: Methods and …, 2022"],"snippet":"Computational linguistics and cognitive linguistics come together when we use data-driven methods to conduct linguistic experiments on corpora. This chapter uses usage-based construction grammar to model geographic variation in language. The basic …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=mpZuEAAAQBAJ&oi=fnd&pg=PA273&dq=commoncrawl&ots=QDhNj-UIiF&sig=Gkw4yCUdjqDM0EjTNJ7mpG44xyA"]}
+{"year":"2022","title":"Combining shallow and deep learning approaches against data scarcity in legal domains","authors":["F Sovrano, M Palmirani, F Vitali - Government Information Quarterly, 2022"],"snippet":"We are recently witnessing a radical shift towards digitisation in many aspects of our daily life, including law, public administration and governance. This has sometimes been done with the aim of reducing costs and human errors by improving data …","url":["https://www.sciencedirect.com/science/article/pii/S0740624X2200048X"]}
+{"year":"2022","title":"Commonsense Validation for Arabic Sentences using Deep Learning","authors":["E Al-Bashabsheh, H Al-Khazaleh, O Elayan, R Duwairi - 2021 22nd International Arab …, 2021"],"snippet":"… -based masked language model trained on a massive 2.5 TB of clean CommonCrawl data. The data includes 100 languages and obtained a decent performance as it … The XLM-Roberta was trained on 2.5 TB of recently produced …","url":["https://ieeexplore.ieee.org/abstract/document/9677156/"]}
+{"year":"2022","title":"Compact N-gram Language Models for Armenian","authors":["DS Karamyan, TS Karamyan - Mathematical Problems of Computer Science, 2022"],"snippet":"Applications such as speech recognition and machine translation use language models to select the most likely translation among many hypotheses. For on-device applications, inference time and model size are just as important as performance. In …","url":["https://www.mpcs.sci.am/index.php/mpcs/article/download/732/549"]}
+{"year":"2022","title":"Company recommendation model: Empowering the accounting system and publicly available data","authors":["R Štrimaitis, P Stefanovič, S Ramanauskaitė… - DAMSS 2022: 13th …, 2022"],"snippet":"[eng] Business management requires constant decision-making. Usually, the selection of suitable partners for collaboration is very intuitive, experience-based skill or requires the usage of data analytics. The most important aspect to get an …","url":["https://vb.vgtu.lt/object/elaba:148377608/148377608.pdf"]}
+{"year":"2022","title":"Comparative Analysis of Cross-lingual Contextualized Word Embeddings","authors":["HS Saadi, V Hangya, T Eder, A Fraser"],"snippet":"Contextualized word embeddings have emerged as the most important tool for performing NLP tasks in a large variety of languages. In order to improve the crosslingual representation and transfer learning quality, contextualized embedding …","url":["https://www.cis.uni-muenchen.de/~fraser/pubs/saadi_mrl2022.pdf"]}
+{"year":"2022","title":"Comparative Analysis of Machine Learning Classifiers for Phishing Detection","authors":["MF Ab Razak, MI Jaya, F Ernawan, A Firdaus… - 2022 6th International …, 2022"],"snippet":"… The source for this dataset is from the University Malaysia of Sarawak, compiled from PhishTank, OpenPhish, Alexa and Common Crawl. One method for detecting new phishing websites is to utilize heuristics such as the URL and CSS detection …","url":["https://ieeexplore.ieee.org/abstract/document/9930531/"]}
+{"year":"2022","title":"Comparative Analysis of Transformer Models on WikiHow Dataset","authors":["D Jadeja, A Khetri, A Mittal, DK Vishwakarma - 2022 International Conference on …, 2022"],"snippet":"Because of the ever-increasing amount of information around us, it has become highly essential to consume it in the most efficient way as possible. Text Summarization is a way of generating a summary for a long piece of text while …","url":["https://ieeexplore.ieee.org/abstract/document/9761043/"]}
+{"year":"2022","title":"Comparative Analysis of Transformers to Support Fine-Grained Emotion Detection in Short-Text Data","authors":["RH Frye, DC Wilson - The International FLAIRS Conference Proceedings, 2022"],"snippet":"… A clean derivation of the CommonCrawl Corpus was used in pretraining XLM-R, with one English version and twelve versions inclusive of other languages. Conneau et al. reported 95.0% accuracy on the SST binary sentiment classification task. Clark …","url":["https://journals.flvc.org/FLAIRS/article/download/130612/133913"]}
+{"year":"2022","title":"Comparative Evaluation of Transformer-Based Nepali Language Models","authors":["SR Tamrakar, C Silpasuwanchai - 2022"],"snippet":"… OSCAR (Open Super-large Crawled Aggregated coRpus) is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the Ungoliant architecture, a high-performance pipeline that provides …","url":["https://www.researchsquare.com/article/rs-2289743/latest.pdf"]}
+{"year":"2022","title":"Comparative Study of Classification Algorithms for Website Phishing Detection on Multiple Datasets","authors":["W Sarasjati, S Rustad, HA Santoso, A Syukur… - 2022 International Seminar …, 2022"],"snippet":"… The legitimate sites are collected from Alexa and Common Crawl, whereas the phishing sites are collected from PhishTank and OpenPhish. Mendeley dataset is different from UCI dataset because it has binary labels for classes. For example, 0 …","url":["https://ieeexplore.ieee.org/abstract/document/9920475/"]}
+{"year":"2022","title":"Comparative Study of Marathi Text Classification Using Monolingual and Multilingual Embeddings","authors":["F Eranpurwala - … Network Technologies and Intelligent Computing: First …, 2022"],"snippet":"… It was trained on Common Crawl and Wikipedia dataset using the CBOW model with position-weighted vocabulary of size 99882. IndicBERT was trained on ALBERT [18] using standard masked language model with vocabulary 200K and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=8v9fEAAAQBAJ&oi=fnd&pg=PA441&dq=commoncrawl&ots=fyNHOEuz9Q&sig=fjU_MoFQFWMcxfuV5Mhyv1Tl15M"]}
+{"year":"2022","title":"Comparative study of text representation and learning for Persian named entity recognition","authors":["MM Abdollah Pour, S Momtazi - ETRI Journal, 2022"],"snippet":"… XLM-R [6] is a multilingual language model trained using a large corpus of CommonCrawl data from 100 languages. XLM-R has been shown to significantly outperform previous multilingual models, for example, the mBERT and XLM models. In addition …","url":["https://onlinelibrary.wiley.com/doi/abs/10.4218/etrij.2021-0269"]}
+{"year":"2022","title":"Comparing Different Approaches for Detecting Hate Speech in Online Portuguese Comments","authors":["BC Matos, RB Santos, P Carvalho, R Ribeiro, F Batista - 11th Symposium on …, 2022"],"snippet":"Online Hate Speech (OHS) has been growing dramatically on social media, which has motivated researchers to develop a diversity of methods for its automated detection. However, the detection of OHS in Portuguese is still little studied. To fill …","url":["https://drops.dagstuhl.de/opus/volltexte/2022/16756/pdf/OASIcs-SLATE-2022-10.pdf"]}
+{"year":"2022","title":"Comparing Emotion and Sentiment Analysis Tools on Italian anti-vaccination for COVID-19 posts","authors":["E Bellodi, A Bertagnon, M Gavanelli - Proceedings of the Sixth Workshop on Natural …, 2022"],"snippet":"Since the beginning of the vaccination campaign against Covid-19 in our country, resistance to vaccination has emerged on the part of a not negligible portion of the Italian population. Emotions (such as sadness, fear, etc.) and the polarity (positive/negative) …","url":["https://ceur-ws.org/Vol-3287/paper9.pdf"]}
+{"year":"2022","title":"Comparison of Different Modeling Techniques for Flemish Twitter Sentiment Analysis","authors":["M Reusens, M Reusens, M Callens, S vanden Broucke… - Analytics, 2022"],"snippet":"… The FastText approach, on the other hand, used Wikipedia and Common Crawl as training data. Common Crawl is a nonprofit company that crawls the web and then makes the obtained data publicly available [34]. It is possible that because our …","url":["https://www.mdpi.com/2813-2203/1/2/9/pdf"]}
+{"year":"2022","title":"Comparison of fuzzy sets based on the concept of imprecision","authors":["J Miliauskaitė, D Kalibatienė - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148957123/148957123.pdf"]}
+{"year":"2022","title":"Comparison of Named Entity Recognition Methods on Real-World and Highly Imbalanced Business Document Datasets","authors":["JC Vásquez-Correa, JR Orozco-Arroyave - Applied Computer Sciences in …, 2022","SA Moreno-Acevedo, D Escobar-Grisales… - Workshop on Engineering …, 2022"],"snippet":"… RoBERTa was pre-trained with 2.5 TB of data from the cleaned Common Crawl corpus [18], which includes text data in 100 different languages and allows for computing text representations in multiple languages. Embeddings from RoBERTa …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=zoedEAAAQBAJ&oi=fnd&pg=PA41&dq=commoncrawl&ots=yJmgKGYOPH&sig=aL9Xc2rF3T8jv2DP7kNa7WHOCok","https://link.springer.com/chapter/10.1007/978-3-031-20611-5_4"]}
+{"year":"2022","title":"Comparison of Semantic Similarity Models on Constrained Scenarios","authors":["R Teixeira, M Antunes, D Gomes, RL Aguiar - Information Systems Frontiers, 2022"],"snippet":"The technological world has grown by incorporating billions of small sensing devices, collecting and sharing large amounts of diversified data over the new generation of wireless and mobile networks. We can use semantic similarity models to help …","url":["https://link.springer.com/article/10.1007/s10796-022-10350-w"]}
+{"year":"2022","title":"Comparison of Text Mining Models for Food and Dietary Constituent Named-Entity Recognition","authors":["N Perera, TTL Nguyen, M Dehmer, F Emmert-Streib - Machine Learning and …, 2022"],"snippet":"Biomedical Named-Entity Recognition (BioNER) has become an essential part of text mining due to the continuously increasing digital archives of biological and medical articles. While there are many well-performing BioNER tools for entities …","url":["https://www.mdpi.com/2504-4990/4/1/12/pdf"]}
+{"year":"2022","title":"Comparison of text preprocessing methods","authors":["CP Chai - Natural Language Engineering, 2022"],"snippet":"Text preprocessing is not only an essential step to prepare the corpus for modeling but also a key area that directly affects the natural language processing (NLP) application results. For instance, precise tokenization increases the accuracy of part-of-speech …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/comparison-of-text-preprocessing-methods/43A20821D65F1C0C4366B126FC794AE3"]}
+{"year":"2022","title":"Compilation and evaluation of the Spanish SatiCorpus 2021 for satire identification using linguistic features and transformers","authors":["JA García-Díaz, R Valencia-García - Complex & Intelligent Systems, 2022"],"snippet":"Satirical content on social media is hard to distinguish from real news, misinformation, hoaxes or propaganda when there are no clues as to which medium these news were originally written in. It is important, therefore, to provide Information Retrieval …","url":["https://link.springer.com/article/10.1007/s40747-021-00625-1"]}
+{"year":"2022","title":"Complex Word Identification for Language Learners","authors":["A Srivastava, C Biemann, Ö Alaçam, X Wang - 2022"],"snippet":"… In my experiment, I used the pre-trained English word vectors from FastText, which contains 2 million word vectors with subword information on Common Crawl (600B tokens). Table 6.3 displays the results achieved by training the sequential model …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2022-ma-srivastava.pdf"]}
+{"year":"2022","title":"Comprehensive Survey: Approaches to Emerging Technologies Detection within Scientific Publications","authors":["A Yelenov, AA Pak, AA A Ziyaden, I Akhmetov… - Computación y Sistemas, 2022"],"snippet":"The identification of breakthrough topics and emerging technologies has been of interest to the governments of many countries and the scientific community since the last century. This study presents the status and trend of the research field through a …","url":["https://cys.cic.ipn.mx/ojs/index.php/CyS/article/viewFile/4424/3458"]}
+{"year":"2022","title":"Compressed FastText Models for Czech Tagger","authors":["Z Nevěřilová - RASLAN 2022 Recent Advances in Slavonic Natural …, 2022"],"snippet":"… Instead of CommonCrawl, we decided to use the SYN corpus, version 9. The SYN corpus [9] … The SYN corpus is therefore about half of the size of the 2017 CommonCrawl used in the … This is surprising since we supposed the training data …","url":["http://nlp.fi.muni.cz/raslan/raslan22.pdf#page=89"]}
+{"year":"2022","title":"COMPS: Conceptual Minimal Pair Sentences for testing Property Knowledge and Inheritance in Pre-trained Language Models","authors":["K Misra, JT Rayz, A Ettinger - arXiv preprint arXiv:2210.01963, 2022"],"snippet":"A characteristic feature of human semantic memory is its ability to not only store and retrieve the properties of concepts observed through experience, but to also facilitate the inheritance of properties (can breathe) from superordinate concepts (animal) to …","url":["https://arxiv.org/pdf/2210.01963"]}
+{"year":"2022","title":"COMPUTATIONAL INFERENCE OF TRUSTWORTHINESS IN SOCIAL FIGURES THROUGH ANALYSIS OF SPEECH ACOUSTIC, TEXTUAL, AND VISUAL SIGNALS","authors":["SMS Shah - 2022"],"snippet":"This chapter provides a general introduction to the field of Social Signal Processing (SSP) and its application areas. It commences by providing a brief description of motivation for this research and use of SSP for behavioural analysis, presenting the research …","url":["https://researchrepository.rmit.edu.au/view/pdfCoverPage?instCode=61RMIT_INST&filePid=13293466670001341&download=true"]}
+{"year":"2022","title":"Computer Vision based Automated Spare Part Finder App","authors":["G Jugroop, P Seegolum, A Chiniah, BB Humaïra - 2022 International Conference on …, 2022"],"snippet":"The “Automated car spare part finder app” aims at building a spare part detection mobile application using image recognition technique that will assist users in finding desired spare parts and provide a list of websites where those spare parts can be …","url":["https://ieeexplore.ieee.org/abstract/document/9792778/"]}
+{"year":"2022","title":"Conceptual framework of data science for good squad","authors":["D Krikščiūnienė, V Sakalauskas, G Romeika - DAMSS 2022: 13th conference on data …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148214567/148214567.pdf"]}
+{"year":"2022","title":"Conditional Generation with a Question-Answering Blueprint","authors":["S Narayan, J Maynez, RK Amplayo, K Ganchev… - arXiv preprint arXiv …, 2022"],"snippet":"The ability to convey relevant and faithful information is critical for many tasks in conditional generation and yet remains elusive for neural seq-to-seq models whose outputs often reveal hallucinations and fail to correctly cover important details. In this …","url":["https://arxiv.org/pdf/2207.00397"]}
+{"year":"2022","title":"Conditional Supervised Contrastive Learning for Fair Text Classification","authors":["J Chi, W Shand, Y Yu, KW Chang, H Zhao, Y Tian - arXiv preprint arXiv:2205.11485, 2022"],"snippet":"… The data consist of nearly 400,000 online biographies collected from the Common Crawl corpus. These biographies are annotated with one of the 28 professions to which their subject belongs. The data are mapped to a binary gender …","url":["https://arxiv.org/pdf/2205.11485"]}
+{"year":"2022","title":"Considerations for Multilingual Wikipedia Research","authors":["I Johnson, E Lescak - arXiv preprint arXiv:2204.02483, 2022"],"snippet":"English Wikipedia has long been an important data source for much research and natural language machine learning modeling. The growth of non-English language editions of Wikipedia, greater computational resources, and calls for equity in the …","url":["https://arxiv.org/pdf/2204.02483"]}
+{"year":"2022","title":"Considerations for the social impact of natural language processing","authors":["AGJ Paullada - 2021"],"snippet":"Natural language processing (NLP) technologies have transformed how people access information and communicate with one another. It has thus become critical to take stock of the social impact of natural language processing technologies. In this …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48281/Paullada_washington_0250E_23796.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Consolidation of Crowd-Sourced Geo-Tagged Data for Parameterized Travel Recommendations","authors":["A Luberg"],"snippet":"The general subject area of this dissertation is automated creation of recommendations for tourism, with the focus on sights and visit-worthy locations. This stands in contrast to the recommendations provided by mainstream travel …","url":["https://scholar.archive.org/work/2pvxz3c6nvdelbkan4y5l5ykdy/access/wayback/https://digikogu.taltech.ee/et/Download/e6d95cdb-97f5-405e-af8a-dd617fa4c922/ConsolidationofCrowdSourcedGeoTaggedDatafor.pdf"]}
+{"year":"2022","title":"Constructing and analyzing domain-specific language model for financial text mining","authors":["M Suzuki, H Sakaji, M Hirano, K Izumi - Information Processing & Management, 2023"],"snippet":"The application of natural language processing (NLP) to financial fields is advancing with an increase in the number of available financial documents. Transformer-based models such as Bidirectional Encoder Representations from Transformers (BERT) …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322002953"]}
+{"year":"2022","title":"Constructing novel datasets for intent detection and ner in a korean healthcare advice system: guidelines and empirical results","authors":["YM Kim, TH Lee, SO Na - Applied Intelligence, 2022"],"snippet":"The demand for intelligent dialogue systems has increased rapidly in recent years. However, building such systems involves numerous complicated processes, including training data construction for language understanding. Although training …","url":["https://link.springer.com/article/10.1007/s10489-022-03400-y"]}
+{"year":"2022","title":"Construction and Evaluation of Sentiment Datasets for Low-Resource Languages: The Case of Uzbek","authors":["C Gómez-Rodrıguez - … Technology. Challenges for Computer Science and …"],"snippet":"To our knowledge, the majority of human language processing technologies for low-resource languages don’t have well-established linguistic resources for the development of sentiment analysis applications. Therefore, it is in dire need of such tools and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=sF1zEAAAQBAJ&oi=fnd&pg=PA232&dq=commoncrawl&ots=DEPUp0f29K&sig=ynTMQqraKZa4eht38ObNrhsNhPw"]}
+{"year":"2022","title":"CONSTRUCTION OF A TRANSLATION TOOL FROM FRENCH TO FALC","authors":["FST TCHATCHOUANG, KW NZOKOU"],"snippet":"We started our internship on 06/06/2021 and ended on the 16/09/2022, which was an opportunity got after a sequence of offers sent by Mr Yasser ALMEHIO amongst which was found the internship at ISEP-école d'ingénieurs du numérique. For this …","url":["https://www.researchgate.net/profile/Tchouanga-Franck/publication/363780793_CONSTRUCTION_OF_A_TRANSLATION_TOOL_FROM_FRENCH_TO_FALC/links/632dc9c56063772afd8919ad/CONSTRUCTION-OF-A-TRANSLATION-TOOL-FROM-FRENCH-TO-FALC.pdf"]}
+{"year":"2022","title":"Context-aware IoT Service Recommendation: A Deep Collaborative Filtering-based Approach","authors":["Z Wang, CA Sun, M Aiello - 2022 IEEE International Conference on Web Services …, 2022"],"snippet":"The advantages of Service-Oriented Architecture (SOA) combined with the emerging and diffusion of the Internet of Things (IoT) instances have given birth to a new paradigm for IoT components integration, ie, Service-Oriented IoT. Microservices …","url":["https://ieeexplore.ieee.org/abstract/document/9885270/"]}
+{"year":"2022","title":"Contextual Answer Validation","authors":["A Baksi - 2022"],"snippet":"… Among these is the Common Crawl dataset[2]. It is acquired via scraping web pages, skipping over any HTML markup. Each month, it generates about 20TB of data via scraping. However, a significant quantity of Common Crawl contains …","url":["http://library.isical.ac.in:8080/xmlui/bitstream/handle/10263/7340/Arkadeep_Thesis-dissertation-18-7-22.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Contextualization and Generalization in Entity and Relation Extraction","authors":["B Taillé - arXiv preprint arXiv:2206.07558, 2022"],"snippet":"During the past decade, neural networks have become prominent in Natural Language Processing (NLP), notably for their capacity to learn relevant word representations from large unlabeled corpora. These word embeddings can then be …","url":["https://arxiv.org/pdf/2206.07558"]}
+{"year":"2022","title":"Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias","authors":["R Wolfe, Y Yang, B Howe, A Caliskan - arXiv preprint arXiv:2212.11261, 2022"],"snippet":"Nine language-vision AI models trained on web scrapes with the Contrastive Language-Image Pretraining (CLIP) objective are evaluated for evidence of a bias studied by psychologists: the sexual objectification of girls and women, which occurs …","url":["https://arxiv.org/pdf/2212.11261"]}
+{"year":"2022","title":"Contrastive Training Improves Zero-Shot Classification of Semi-structured Documents","authors":["M Khalifa, Y Vyas, S Wang, G Horwood, S Mallya… - arXiv preprint arXiv …, 2022"],"snippet":"… B Pre-training data from Common Crawl We build our pre-training corpus by first extracting all documents from CommonCrawl with a ‘.pdf‘ extension. We then remove duplicate documents based on the MD5 hash using fdupes.. The resulting …","url":["https://arxiv.org/pdf/2210.05613"]}
+{"year":"2022","title":"Controlling Formality in Low-Resource NMT with Domain Adaptation and Re-Ranking: SLT-CDT-UoS at IWSLT2022","authors":["ST Vincent, L Barrault, C Scarton - arXiv preprint arXiv:2205.05990, 2022"],"snippet":"This paper describes the SLT-CDT-UoS group's submission to the first Special Task on Formality Control for Spoken Language Translation, part of the IWSLT 2022 Evaluation Campaign. Our efforts were split between two fronts: data engineering …","url":["https://arxiv.org/pdf/2205.05990"]}
+{"year":"2022","title":"Conversational Humor Analysis: Developing Data, Annotation Schema and Models","authors":["V Pamulapati - 2021"],"snippet":"Conversational humor (CH) is a sub-domain of humor where the participants (speakers or listeners) engage in different types of humor such as retorts or teasing for various purposes. There are shared complexities between this phenomenon and the larger …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.8971852bf2270413.76616973686e6176695f70616d756c61706174695f66696e616c5f7468657369732e706466.pdf"]}
+{"year":"2022","title":"Core words in semantic representation","authors":["A Wang, S De Deyne, M McKague, A Perfors - Proceedings of the Annual Meeting of …, 2022"],"snippet":"A central question in cognitive science is how semantic information is mentally represented. Two dominant theories of semantic representation are language-based distributional semantic models (which suggest that word meaning is based on which …","url":["https://escholarship.org/content/qt8t34p5t8/qt8t34p5t8.pdf"]}
+{"year":"2022","title":"Correcting diacritics and typos with ByT5 transformer model","authors":["L Stankevičius, M Lukoševičius, J Kapočiūtė-Dzikienė… - arXiv preprint arXiv …, 2022"],"snippet":"… Good examples of the first side are the Common Crawl dataset of more than 20TB of data and its version OSCAR [107] filtered by language. Such huge datasets are now one of the main building blocks of popular transformer model pre-training but …","url":["https://arxiv.org/pdf/2201.13242"]}
+{"year":"2022","title":"CoSearcher: studying the effectiveness of conversational search refinement and clarification through user simulation","authors":["A Salle, S Malmasi, O Rokhlenko, E Agichtein - Information Retrieval Journal, 2022"],"snippet":"A key application of conversational search is refining a user’s search intent by asking a series of clarification questions, aiming to improve the relevance of search results. Training and evaluating such conversational systems currently requires …","url":["https://link.springer.com/article/10.1007/s10791-022-09404-z"]}
+{"year":"2022","title":"Cost-Effective Updating of Distributed Reordered Indexes","authors":["J Mackenzie, A Moffat - 2021"],"snippet":"Index reordering techniques allow document collections to be renumbered, with the goal of developing a permutation of the initial document ordinal identifiers that places documents that are (somehow) like each other into positions near each other …","url":["https://jmmackenzie.io/pdf/mm21-adcs.pdf"]}
+{"year":"2022","title":"COVID vaccine stigma: detecting stigma across social media platforms with computational model based on deep learning","authors":["N Straton - Applied Intelligence, 2022"],"snippet":"The study presents the first computational model of COVID vaccine stigma that can identify stigmatised sentiment with a high level of accuracy and generalises well across a number of social media platforms. The aim of the study is to understand the …","url":["https://link.springer.com/article/10.1007/s10489-022-04311-8"]}
+{"year":"2022","title":"COVID-19 and cyberbullying: deep ensemble model to identify cyberbullying from code-switched languages during the pandemic","authors":["S Paul, S Saha, JP Singh - Multimedia Tools and Applications, 2022"],"snippet":"… We have experimented with two different language specific fasttext Footnote 6 word embeddings, ie, English and Hindi as our code-switched corpus contains aforementioned two languages which are trained on Common Crawl and Wikipedia …","url":["https://link.springer.com/article/10.1007/s11042-021-11601-9"]}
+{"year":"2022","title":"COVID-19 Tweets Classification Based on a Hybrid Word Embedding Method. Big Data Cogn. Comput. 2022, 6, 58","authors":["Y Didi, A Walha, A Wali - 2022"],"snippet":"… pre-trained Word2Vec, FastText, and GloVe embedding trained on Common Crawl and Wikipedia with 300-D vectors, for word embedding. … vectors freely available on corpora, which is the combination of Gigaword5 and Wikipedia2014 …","url":["https://www.researchgate.net/profile/Yosra-Didi/publication/360686590_COVID-19_Tweets_Classification_Based_on_a_Hybrid_Word_Embedding_Method/links/62877bdb8ecbaa07fcc54606/COVID-19-Tweets-Classification-Based-on-a-Hybrid-Word-Embedding-Method.pdf"]}
+{"year":"2022","title":"Cramming: Training a Language Model on a Single GPU in One Day","authors":["J Geiping, T Goldstein - arXiv preprint arXiv:2212.14034, 2022"],"snippet":"Recent trends in language modeling have focused on increasing performance through scaling, and have resulted in an environment where training language models is out of reach for most researchers and practitioners. While most in the …","url":["https://arxiv.org/pdf/2212.14034"]}
+{"year":"2022","title":"Crawling Under-Resourced Languages–A Portal for Community-Contributed Corpus Collection","authors":["E Körner, F Helfer, C Schröder, T Eckart, D Goldhahn"],"snippet":"… The full texts might also be contained and accessible in larger web crawls and collections such as archive.org or commoncrawl.org. To alleviate the likelihood of copyright and license infringement, the largest related text segments published are …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/DCLRL/pdf/2022.dclrl-1.5.pdf"]}
+{"year":"2022","title":"Creating a Large Language Model of a Philosopher","authors":["E Schwitzgebel, D Schwitzgebel, A Strasser"],"snippet":"Can large language models be trained to produce philosophical texts that are difficult to distinguish from texts produced by human philosophers? To address this question, we fine-tuned OpenAI’s GPT-3 with two sets of training data: the blog posts …","url":["http://www.faculty.ucr.edu/~eschwitz/SchwitzPapers/GPT-3-Dennett-221102.pdf"]}
+{"year":"2022","title":"CRIM's Speech Recognition system description for OpenASR21 evaluation","authors":["V Gupta, G Boulianne"],"snippet":"CRIM participated in all the 15 low resource languages and the three languages with case sensitive scoring in the OpenASR21 Challenge for the constrained condition. For acoustic modeling, we developed both hybrid DNN-HMM systems and …","url":["https://www.nist.gov/document/crim-openasr21-system-description"]}
+{"year":"2022","title":"CRIM's Speech Recognition System for OpenASR21 Evaluation with Conformer and Voice Activity Detector Embeddings","authors":["V Gupta, G Boulianne - International Conference on Speech and Computer, 2022"],"snippet":"CRIM participated in all the 15 low resource languages and the three languages with case sensitive scoring in OpenASR21 for the constrained condition. For acoustic modeling, we developed both hybrid DNN-HMM systems and a conformer …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20980-2_21"]}
+{"year":"2022","title":"Cross-Language Learning for Product Matching","authors":["R Peeters, C Bizer - 2022"],"snippet":"… As multilingual models, we use multi-lingual BERT (’bert-base-multilingual-uncased’), which is trained on the top 100 largest Wikipedias, as well as XLMRoBERTa (’xlm-roberta-base’), which is trained on a CommonCrawl corpus consisting of 100 different languages …","url":["https://www2022.thewebconf.org/PaperFiles/48.pdf"]}
+{"year":"2022","title":"Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure","authors":["Y Chai, Y Liang, N Duan - arXiv preprint arXiv:2203.08430, 2022"],"snippet":"Multilingual pre-trained language models, such as mBERT and XLM-R, have shown impressive cross-lingual ability. Surprisingly, both of them use multilingual masked language model (MLM) without any cross-lingual supervision or aligned data …","url":["https://arxiv.org/pdf/2203.08430"]}
+{"year":"2022","title":"Cross-Lingual and Cross-Domain Crisis Classification for Low-Resource Scenarios","authors":["C Sánchez, H Sarmiento, J Pérez, A Abeliuk, B Poblete - arXiv preprint arXiv …, 2022"],"snippet":"Social media data has emerged as a useful source of timely information about real-world crisis events. One of the main tasks related to the use of social media for disaster management is the automatic identification of crisis-related messages. Most of the …","url":["https://arxiv.org/pdf/2209.02139"]}
+{"year":"2022","title":"Cross-Lingual Approaches to Identifying Argument Components and Relations in Norwegian Reviews","authors":["Y Khutarniuk - 2022"],"snippet":"Argument mining is the process of automatic extraction of certain argumentation structures from data. Argument mining consists of several stages such as argument component detection, argument component classification, and argumentative …","url":["https://www.duo.uio.no/bitstream/handle/10852/94450/yauhenk_master_thesis.pdf?sequence=5"]}
+{"year":"2022","title":"Cross-lingual Coreference Resolution and Neural Machine Translation","authors":["JF Hetzer - 2022"],"snippet":"Like many other Natural Language Processing (NLP) tasks, coreference resolution has benefited massively from new developments in recent years. Deeper and more complex architectures enabled coreference resolution systems that work end-to-end …","url":["https://isl.anthropomatik.kit.edu/downloads/Jannik%20Hetzer%20Master%20Arbeit.pdf"]}
+{"year":"2022","title":"Cross-lingual transfer of knowledge in distributional language models: Experiments in Hungarian","authors":["A Novák, B Novák - Acta Linguistica Academica, 2022"],"snippet":"In this paper, we argue that the very convincing performance of recent deep-neural-model-based NLP applications has demonstrated that the distributionalist approach to language description has proven to be more successful than the earlier subtle rule-based …","url":["https://akjournals.com/view/journals/2062/aop/article-10.1556-2062.2022.00580/article-10.1556-2062.2022.00580.xml"]}
+{"year":"2022","title":"Cross-Modal Recurrent Semantic Comprehension for Referring Image Segmentation","authors":["C Shang, H Li, H Qiu, Q Wu, F Meng, T Zhao, KN Ngan - IEEE Transactions on …, 2022"],"snippet":"… For language encoder, we adopt a vanilla GRU [20] and initialize the word embeddings by GloVe [65] pretrained on Common Crawl 840B. The input images are resized to 416×416. The maximum length of language expression is set to 15 in …","url":["https://ieeexplore.ieee.org/abstract/document/9998537/"]}
+{"year":"2022","title":"Crosslingual Sharing for Low-Resource Natural Language Processing","authors":["P Mulcaire - 2022"],"snippet":"… Common Crawl, a repository of content scraped from the web which is frequently used as a source of text data, includes text from hundreds of languages—but more than 45% of the documents crawled are in English, just ten languages together …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48884/Mulcaire_washington_0250E_24163.pdf?sequence=1"]}
+{"year":"2022","title":"CrossQE: HW-TSC 2022 Submission for the Quality Estimation Shared Task","authors":["S Tao, C Su, M Ma, H Yang, M Zhang, X Geng…"],"snippet":"Quality estimation (QE) is a crucial method to investigate automatic methods for estimating the quality of machine translation results without reference translations. This paper presents Huawei Translation Services Center’s (HWTSC’s) work called …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.61.pdf"]}
+{"year":"2022","title":"Current Research in Ecological and Social Psychology","authors":["M Atari, NK Reimer, J Graham, J Hoover, B Kennedy…"],"snippet":"Infectious diseases have been an impending threat to the survival of individuals and groups throughout our evolutionary history. As a result, humans have developed psychological pathogen-avoidance mechanisms and groups have developed …","url":["https://www.researchgate.net/profile/Mohammad-Atari-3/publication/362589037_Pathogens_Are_Linked_to_Human_Moral_Systems_Across_Time_and_Space/links/62ff8f10aa4b1206fac139f7/Pathogens-Are-Linked-to-Human-Moral-Systems-Across-Time-and-Space.pdf"]}
+{"year":"2022","title":"Customer Support Chat Intent Classification using Weak Supervision and Data Augmentation","authors":["S Prabhu, AK Brahma, H Misra - 5th Joint International Conference on Data Science …, 2022"],"snippet":"Understanding the actual intent of customers is an essential step in automating the conversational experience on a chat platform. Typically, chatbots are powered by machine learning algorithms that rely on the acquisition of a large amount of high …","url":["https://dl.acm.org/doi/abs/10.1145/3493700.3493729"]}
+{"year":"2022","title":"Cyber-Phishing Website Detection Using Fuzzy Rule Interpolation","authors":["M Almseidin, M Alkasassbeh, M Alzubi, J Al-Sawwa - Cryptography, 2022"],"snippet":"This paper introduces a novel detection method for phishing website attacks while avoiding the issues associated with the deficiencies of the knowledge-based representation and the binary decision. The suggested detection method was …","url":["https://www.mdpi.com/2410-387X/6/2/24/pdf?version=1651912543"]}
+{"year":"2022","title":"Data Analytics and Modeling in IoT-Fog Environment for Resourceconstrained IoT-Applications: A Review","authors":["O Farooq, P Singh - Recent Advances in Computer Science and …, 2022"],"snippet":"Objective: The emergence of the concepts like Big Data, Data Science, Machine Learning (ML), and the Internet of Things (IoT) in recent years has added the potential of research in today's world. The continuous use of IoT devices, sensors, etc …","url":["https://www.ingentaconnect.com/content/ben/rascs/2022/00000015/00000007/art00008"]}
+{"year":"2022","title":"Data Augmentation for Automated Essay Scoring using Transformer Models","authors":["K Gupta"],"snippet":"Automated essay scoring is one of the most important problem in Natural Language Processing. It has been explored for a number of years, and it remains partially solved. In addition to its economic and educational usefulness, it presents research …","url":["https://www.researchgate.net/profile/Kshitij_Gupta30/publication/364689774_Data_Augmentation_for_Automated_Essay_Scoring_using_Transformer_Models/links/636a743d37878b3e87913dcc/Data-Augmentation-for-Automated-Essay-Scoring-using-Transformer-Models.pdf"]}
+{"year":"2022","title":"Data Augmentation for Inline Tag-Aware Neural Machine Translation","authors":["Y Ryu, Y Choi, S Kim"],"snippet":"Despite the wide use of inline formatting, not much has been studied on translating sentences with inline formatted tags. The detag-andproject approach using word alignments is one solution to translating a tagged sentence. However, the method …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.81.pdf"]}
+{"year":"2022","title":"Data Augmentation for Intent Classification of German Conversational Agents in the Finance Domain","authors":["S Rentschler, M Riedl, C Stab, M Rückert - Proceedings of the 18th Conference on …, 2022"],"snippet":"In this paper, we focus on improving the intent recognition for a conversational agent. For languages other than English, labeled data needed for training is often limited. Limitations rise even more when moving to specific domains. Here, our goal is to …","url":["https://aclanthology.org/2022.konvens-1.1.pdf"]}
+{"year":"2022","title":"Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation","authors":["A Fernando, S Ranathunga - arXiv preprint arXiv:2205.08722, 2022"],"snippet":"Out-of-Vocabulary (OOV) is a problem for Neural Machine Translation (NMT). OOV refers to words with a low occurrence in the training data, or to those that are absent from the training data. To alleviate this, word or phrase-based Data Augmentation (DA) …","url":["https://arxiv.org/pdf/2205.08722"]}
+{"year":"2022","title":"Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages","authors":["M Das, S Banerjee, A Mukherjee - arXiv preprint arXiv:2204.12543, 2022"],"snippet":"Abusive language is a growing concern in many social media platforms. Repeated exposure to abusive speech has created physiological effects on the target users. Thus, the problem of abusive language should be addressed in all forms for online …","url":["https://arxiv.org/pdf/2204.12543"]}
+{"year":"2022","title":"Data Efficient Multilingual Natural Language Processing","authors":["X Wang - 2022"],"snippet":"… ; the top five languages in CommonCrawl, a popular source of web-crawled data for the development of NLP models, account for about 70% of the total data, while the majority of languages in the world have much less data or no data at all in …","url":["https://www.lti.cs.cmu.edu/sites/default/files/wang%2C%20cindy%20-%20Thesis.pdf"]}
+{"year":"2022","title":"Data Governance in the Age of Large-Scale Data-Driven Language Technology","authors":["Y JERNITE, HUU NGUYEN, S BIDERMAN, A ROGERS… - 2022"],"snippet":"New families of algorithms relying on deep learning have made it possible to extract ever more complex language statistics from growing numbers of text and speech records to drastically improve the performance and applicability of data-driven …","url":["https://yjernite.github.io/content/LangDataGov.pdf"]}
+{"year":"2022","title":"Data integration and ethical quality: fundamental steps of the data analysis pipeline","authors":["F Azzalini - 2022"],"snippet":"… and the corpus on which it was trained is Common Crawl2. Regarding GloVe we use the model glove.840B.300d [106] and again each word is represented as a 300-dimensional vector and the training corpus was still Common Crawl. Once the single words are …","url":["https://www.politesi.polimi.it/bitstream/10589/187689/1/Azzalini%20Fabio%20PhD%20Thesis%20-%20POLITESI.pdf"]}
+{"year":"2022","title":"Data paper","authors":["W Tongjing, Z Yin, Z Bao, E Meijers"],"snippet":"… The dataset was extracted from Common Crawl, a web archive, which has periodically crawled … We used the entire Common Crawl text archive of April 2019 for processing and conducting … We subsequently used the entire Common Crawl …","url":["https://www.researchgate.net/profile/Evert-Meijers/publication/362952059_Dataset_of_intercity_relationships_between_293_Chinese_cities_extracted_and_classified_on_the_basis_of_toponym_co-occurrences_on_Common_Crawl/links/6308bfc25eed5e4bd11f7938/Dataset-of-intercity-relationships-between-293-Chinese-cities-extracted-and-classified-on-the-basis-of-toponym-co-occurrences-on-Common-Crawl.pdf"]}
+{"year":"2022","title":"Data Selection Curriculum for Neural Machine Translation","authors":["T Mohiuddin, P Koehn, V Chaudhary, J Cross… - arXiv preprint arXiv …, 2022"],"snippet":"… In our experiments, we use the newscrawl data as in-domain and commoncrawl data combined with newscrawl as general-domain for training the LMs. After scoring each parallel sentence pair (xi,yi) ∈ Dd by any of the above methods, we rank Dd …","url":["https://arxiv.org/pdf/2203.13867"]}
+{"year":"2022","title":"Data-Centric Debugging: mitigating model failures via targeted data collection","authors":["S Singla, AM Chegini, M Moayeri, S Feiz - arXiv preprint arXiv:2211.09859, 2022"],"snippet":"Deep neural networks can be unreliable in the real world when the training set does not adequately cover all the settings where they are deployed. Focusing on image classification, we consider the setting where we have an error distribution $\\mathcal{E} …","url":["https://arxiv.org/pdf/2211.09859"]}
+{"year":"2022","title":"Data-Driven Natural Language Inference","authors":["Y Nie - 2022"],"snippet":"Natural Language Inference (NLI) research involves the development of models that can mimic human inference processes based on natural language and classify the inference relation between sentences. For example, given the premise that “In 2019 …","url":["https://search.proquest.com/openview/2df1409d8beb3f8ab2883f74138fa258/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Database Systems for Advanced Applications: 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part III","authors":["A Bhattacharya, JLM Li, D Agrawal, PK Reddy… - 2022"],"snippet":"The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=4XtsEAAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=GfE_2IqJct&sig=IIumPcUnOioFQO9gemsHu9RotXc"]}
+{"year":"2022","title":"Datasheet for the Pile","authors":["S Biderman, K Bicheno, L Gao - arXiv preprint arXiv:2201.07311, 2022"],"snippet":"This datasheet describes the Pile, a 825 GiB dataset of human-authored text compiled by EleutherAI for use in large-scale language modeling. The Pile is comprised of 22 different text sources, ranging from original scrapes done for this …","url":["https://arxiv.org/pdf/2201.07311"]}
+{"year":"2022","title":"DBkWik++--Multi Source Matching of Knowledge Graphs","authors":["S Hertling, H Paulheim - arXiv preprint arXiv:2210.02864, 2022"],"snippet":"Large knowledge graphs like DBpedia and YAGO are always based on the same source, ie, Wikipedia. But there are more wikis that contain information about long-tail entities such as wiki hosting platforms like Fandom. In this paper, we present the …","url":["https://arxiv.org/pdf/2210.02864"]}
+{"year":"2022","title":"Dead or Murdered? Predicting Responsibility Perception in Femicide News Reports","authors":["G Minnema, S Gemelli, C Zanchi, T Caselli, M Nissim - arXiv preprint arXiv …, 2022"],"snippet":"Different linguistic expressions can conceptualize the same event from different viewpoints by emphasizing certain participants over others. Here, we investigate a case where this has social consequences: how do linguistic expressions of gender-based …","url":["https://arxiv.org/pdf/2209.12030"]}
+{"year":"2022","title":"Debiasing isn't enough!--On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Tasks","authors":["M Kaneko, D Bollegala, N Okazaki - arXiv preprint arXiv:2210.02938, 2022"],"snippet":"We study the relationship between task-agnostic intrinsic and task-specific extrinsic social bias evaluation measures for Masked Language Models (MLMs), and find that there exists only a weak correlation between these two types of evaluation measures …","url":["https://arxiv.org/pdf/2210.02938"]}
+{"year":"2022","title":"Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features","authors":["C Du, K Fu, J Li, H He - arXiv preprint arXiv:2210.06756, 2022"],"snippet":"… several studies have addressed the idea of decoding naturalistic visual experiences from brain activity using purely linguistic features [15], [16], they merely use standard word vectors of class names that are automatically extracted from large …","url":["https://arxiv.org/pdf/2210.06756"]}
+{"year":"2022","title":"Deep cascaded multitask framework for detection of temporal orientation, sentiment and emotion from suicide notes","authors":["S Ghosh, A Ekbal, P Bhattacharyya - Scientific Reports, 2022"],"snippet":"… To capture the syntactic and semantic information of the words in a phrase, we use the efficacy of a 300-dimensional pre-trained GloVe word embedding 51 that is trained on the Common Crawl (42 billion tokens) corpus. …","url":["https://www.nature.com/articles/s41598-022-08438-z"]}
+{"year":"2022","title":"Deep Learning Approach for Aspect-Based Sentiment Analysis of Restaurants Reviews in Spanish","authors":["BC Martínez-Seis, O Pichardo-Lagunas, S Miranda… - Computación y Sistemas, 2022"],"snippet":"Online reviews of products and services have become important for customers and enterprises. Recent research focuses on analyzing and managing those kinds of reviews using natural language processing. This paper focuses on aspect-based …","url":["https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/download/4258/3387"]}
+{"year":"2022","title":"Deep learning based semantic textual similarity for applications in translation technology","authors":["T Ranasinghe - 2021"],"snippet":"Semantic Textual Similarity (STS) measures the equivalence of meanings between two textual segments. It is a fundamental task for many natural language processing applications. In this study, we focus on employing STS in the context of translation …","url":["https://wlv.openrepository.com/bitstream/handle/2436/624530/Ranasinghe_PhD_Thesis.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Deep Learning in Sentiment Analysis: A Survey of Recent Architectures","authors":["T Abdullah, A Ahmet - ACM Computing Surveys (CSUR), 2022"],"snippet":"Humans are increasingly integrated with devices that enable the collection of vast unstructured opinionated data. Accurately analysing subjective information from this data is the task of sentiment analysis (an actively researched area in NLP). Deep …","url":["https://dl.acm.org/doi/abs/10.1145/3548772"]}
+{"year":"2022","title":"DEEP LEARNING-BASED DEPENDENCY PARSING FOR TURKISH","authors":["SB Ozates - 2022"],"snippet":"… While XLM-R is pretrained on 2.5TB of unlabeled text data across 100 languages extracted from CommonCrawl Corpus [48], the multilingual version of BERT is pretrained on a much smaller Wikipedia Corpus for 104 languages. Another …","url":["https://www.cmpe.boun.edu.tr/~gungort/theses/Deep%20Learning-based%20Dependency%20Parsing%20for%20Turkish.pdf"]}
+{"year":"2022","title":"Deep Lexical Hypothesis: Identifying personality structure in natural language","authors":["A Cutler, DM Condon - 2022"],"snippet":"Recent advances in natural language processing (NLP) have produced general models that can perform complex tasks such as summarizing long passages and translating across languages. Here, we introduce a method to extract adjective …","url":["https://psyarxiv.com/gdm5v/download?format=pdf"]}
+{"year":"2022","title":"Deepfake Text Detection: Limitations and Opportunities","authors":["J Pu, Z Sarwar, SM Abdullah, A Rehman, Y Kim…"],"snippet":"… This generator is trained on the RealNews dataset [8], a large corpus (120GB) of news articles from Common Crawl [35]. The GPT-2 model is … [35] “Common crawl: A nonprofit 501 organization that crawls the web and freely provides its archives and …","url":["https://jmpu.github.io/files/Deepfake%20Text%20Detection%20Limitations%20and%20Opportunities_CR.pdf"]}
+{"year":"2022","title":"Delivering Fairness in Human Resources AI: Mutual Information to the Rescue","authors":["L Hemamou, W Coleman - Proceedings of the 2nd Conference of the Asia-Pacific …, 2022"],"snippet":"Automatic language processing is used frequently in the Human Resources (HR) sector for automated candidate sourcing and evaluation of resumes. These models often use pre-trained language models where it is difficult to know if possible biases …","url":["https://aclanthology.org/2022.aacl-main.64.pdf"]}
+{"year":"2022","title":"Demographic-Aware Language Model Fine-tuning as a Bias Mitigation Technique","authors":["A Garimella, A Amarnath, R Mihalcea"],"snippet":"BERT-like language models (LMs), when exposed to large unstructured datasets, are known to learn and sometimes even amplify the biases present in such data. These biases generally reflect social stereotypes with respect to gender, race, age …","url":["https://web.eecs.umich.edu/~mihalcea/papers/garimella.aacl22.pdf"]}
+{"year":"2022","title":"Demonstrator of Automatic Minuting","authors":["M Singh, R Kumar, T Ghosal, O Bojar, CC PV, AS PV… - 2022"],"snippet":"… framework to suit a variety of challenges in the domain of natural language understanding T5 also explained the advantage of scaling up the model size (to 11B parameters) and pre-training corpus, by introducing C4 (a massive text corpus which …","url":["https://elitr.eu/wp-content/uploads/2022/03/D65.FINAL_.pdf"]}
+{"year":"2022","title":"Demystifying Prompts in Language Models via Perplexity Estimation","authors":["H Gonen, S Iyer, T Blevins, NA Smith, L Zettlemoyer - arXiv preprint arXiv:2212.04037, 2022"],"snippet":"Language models can be prompted to perform a wide variety of zeroand few-shot learning problems. However, performance varies significantly with the choice of prompt, and we do not yet understand why this happens or how to pick the best …","url":["https://arxiv.org/pdf/2212.04037"]}
+{"year":"2022","title":"Dense-to-Sparse Gate for Mixture-of-Experts","authors":["X Nie, S Cao, X Miao, L Ma, J Xue, Y Miao, Z Yang… - arXiv preprint arXiv …, 2021"],"snippet":"… Wikipedia is a single domain of text, which contains about 2,500 words, and WebText is a large and diverse dataset in various domains, which is collected using 45 million links from Common Crawl. We apply GPT2-BPE (vocabulary size of 50257) …","url":["https://arxiv.org/pdf/2112.14397"]}
+{"year":"2022","title":"DESIGN AND IMPLEMENTATION OF A REALWORLD SEARCH ENGINE BASED ON OKAPI BM25 AND SENTENCEBERT","authors":["L Bonetti, P Torroni"],"snippet":"The work conducted in this thesis aims to present an hybrid model for a real world application search engine. The project presented was part of an intern ship work carried out in a startup which deals with Knowledge Management and Artificial …","url":["https://amslaurea.unibo.it/24774/1/Thesis_Bonetti.pdf"]}
+{"year":"2022","title":"Design of an GIS-based Investment Heatmap System using Topic Classification and NER","authors":["TT Van, KV Sy, TT Anh, TL Quang, PH Xuan, HL Viet… - 2021 13th International …, 2021"],"snippet":"… A multilingual fastText model [7], pre-trained on Common Crawl and Wikipedia corpus, is used to train on our collected corpus using transfer learning approach. The model was trained using CBOW with position-weights, in dimension 300, with …","url":["https://ieeexplore.ieee.org/abstract/document/9648730/"]}
+{"year":"2022","title":"Design of Oral English Intelligent Evaluation System Based on DTW Algorithm","authors":["Y Fang - Mobile Networks and Applications, 2022"],"snippet":"The accuracy of the existing spoken English intelligent evaluation system is not high, and the spoken English evaluation effect is poor. To improve the accuracy and speed of spoken English evaluation, this paper puts forward the design and …","url":["https://link.springer.com/article/10.1007/s11036-022-01925-7"]}
+{"year":"2022","title":"Designing Machine Learning Systems","authors":["C Huyen - 2022"],"snippet":"Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=EThwEAAAQBAJ&oi=fnd&pg=PT51&dq=commoncrawl&ots=puuVz2C8kK&sig=TP64dzZehXbV5rEytHJY3Yhl3ow"]}
+{"year":"2022","title":"Detecting ambiguity in conversational systems","authors":["A Banerjee - 2021"],"snippet":"The question of detection of user search queries has been explored by many authors. With the advent of speech based search interfaces, narrowing down the scope of search based on user intent becomes even more important. A prominent part of …","url":["https://elib.uni-stuttgart.de/bitstream/11682/11953/1/Banerjee_Master%20Thesis.pdf"]}
+{"year":"2022","title":"Detecting autism from picture book narratives using deep neural utterance embeddings","authors":["A Wawer, I Chojnicka - International Journal of Language & Communication …, 2022"],"snippet":"… Pre-training of ELMoForManyLangs was performed on a 20 million-word data set sampled from Wikipedia and Common Crawl. For each input utterance, the representation obtained from ELMo was a vector of 1024 elements. The vectors …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/1460-6984.12731"]}
+{"year":"2022","title":"Detecting Backdoors in Deep Text Classifiers","authors":["Y Guo, J Wang, T Cohn - arXiv preprint arXiv:2210.11264, 2022"],"snippet":"Deep neural networks are vulnerable to adversarial attacks, such as backdoor attacks in which a malicious adversary compromises a model during training such that specific behaviour can be triggered at test time by attaching a specific word or …","url":["https://arxiv.org/pdf/2210.11264"]}
+{"year":"2022","title":"Detecting explicit lyrics: a case study in Italian music","authors":["M Rospocher - Language Resources and Evaluation, 2022"],"snippet":"Preventing the reproduction of songs whose textual content is offensive or inappropriate for kids is an important issue in the music industry. In this paper, we investigate the problem of assessing whether music lyrics contain content unsuitable …","url":["https://link.springer.com/article/10.1007/s10579-022-09595-3"]}
+{"year":"2022","title":"Detecting Psychological Phenomena in Dialogues","authors":["MO SOTOLAR - 2022"],"snippet":"Instant messaging (IM) is a type of online communication that allows for the synchronous exchange of text, images, voice, and videos between two or more people [1] using applications and platforms, such as Messenger or WhatsApp. This …","url":["https://is.muni.cz/th/x42fc/sotolar_teze_clanky_Archive.pdf"]}
+{"year":"2022","title":"Detection and Performance Evaluation of Online-Fraud Using Deep Learning Algorithms","authors":["A Khan, M Patil - Intelligent Computing and Networking, 2022"],"snippet":"Online News Portals are currently one of the primary sources used by people, though its credibility is under serious question. Because the problem associated with this is Click-bait. Click-baiting being the growing phenomenon on internet has the …","url":["https://link.springer.com/chapter/10.1007/978-981-16-4863-2_16"]}
+{"year":"2022","title":"Detection and Prevention of Sophisticated Cyberattacks","authors":["P Zhang - 2022"],"snippet":"Despite extensive research by the security community, cyberattacks such as phishing and Internet of Things (IoT) attacks remain profitable to criminals and continue to cause substantial damage not only to the victim users that they target …","url":["https://search.proquest.com/openview/3fdbd0bb47f35012a7243652fa10f045/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Detection of Bangla Hate Comments and Cyberbullying in Social Media Using NLP and Transformer Models","authors":["M Emon, I Haque, KN Iqbal, M Mehedi, H Kabir… - International Conference on …, 2022"],"snippet":"Hate speech and cyberbullying detection on social media is one of the most trending natural language processing tasks in the current scenario. However, due to the lack of resources, a few work has been done in detection of cyberbullying in social media …","url":["https://link.springer.com/chapter/10.1007/978-3-031-12638-3_8"]}
+{"year":"2022","title":"Detection of dangerous events on social media: a critical review","authors":["ML Jamil, S Pais, J Cordeiro - Social Network Analysis and Mining, 2022"],"snippet":"… The additional data includes the CommonCrawl News dataset (63 million articles, 76 GB), Web text corpus (38 GB), and Stories from Common Crawl (31 GB). This, combined with a massive 1024 V100 Tesla GPU’s running for a day, resulting in pre-training …","url":["https://link.springer.com/article/10.1007/s13278-022-00980-y"]}
+{"year":"2022","title":"Detection of prosodic boundaries in speech using Wav2Vec 2.0","authors":["M Kunešová, M Řezáčková - International Conference on Text, Speech, and …, 2022"],"snippet":"Prosodic boundaries in speech are of great relevance to both speech synthesis and audio annotation. In this paper, we apply the wav2vec 2.0 framework to the task of detecting these boundaries in speech signal, using only acoustic information. We …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_31"]}
+{"year":"2022","title":"Developing a battery of measures for unobtrusive indicators of organisational culture: a research","authors":["TW Reader, A Gillespie - 2022"],"snippet":"… Then, using word embeddings based Common Crawl (2.6 unannotated billion web pages; 840 billion occurrences of 2.2 million unique tokens or words) and OntoNotes 5 (2.9 million annotated words), lists of similar words were generated for …","url":["https://scholar.archive.org/work/ot4molvh5bbmtmyupzmsijv5b4/access/wayback/https://www.tandfonline.com/doi/pdf/10.1080/13669877.2022.2108116?needAccess=true"]}
+{"year":"2022","title":"Developing a general-purpose clinical language inference model from a large corpus of clinical notes","authors":["M Sushil, D Ludwig, AJ Butte, VA Rudrapatna - arXiv preprint arXiv:2210.06566, 2022"],"snippet":"Several biomedical language models have already been developed for clinical language inference. However, these models typically utilize general vocabularies and are trained on relatively small clinical corpora. We sought to evaluate the impact …","url":["https://arxiv.org/pdf/2210.06566"]}
+{"year":"2022","title":"Developing a news classifier for Greek using BERT","authors":["G Gkolfopoulos, I Varlamis - 2022 7th South-East Europe Design Automation …, 2022"],"snippet":"Text categorization is a significant task in the re-search field of text mining, which has recently benefited from deep neural network algorithms and advanced learning techniques that extract language models from large textual corpora. These Pre-Trained …","url":["https://ieeexplore.ieee.org/abstract/document/9932996/"]}
+{"year":"2022","title":"Developing disinformation detection models in low-resource contexts: Czech news article dataset for source-level credibility","authors":["M Bohácek"],"snippet":"… To first obtain URLs of sites with individual articles from those domains, we used the Commoncrawl API 1. We specified for the API to include only articles discovered between January 2019 and September 2021. Once these 1Commoncrawl library …","url":["https://data.matsworld.io/research/cnsc-paper-bohacek.pdf"]}
+{"year":"2022","title":"Developing Technology Tools to Combat Fake Science","authors":["C Impey, A Danehy - Future of Information and Communication Conference, 2022"],"snippet":"… In the next phase of the project, this technology will be scaled to large samples of content drawn from CommonCrawl, and it will be applied across more domains of science. Then it will be deployed as a web browser extension that presents the …","url":["https://link.springer.com/chapter/10.1007/978-3-030-98012-2_25"]}
+{"year":"2022","title":"Development of lumbar spine MRI referrals vetting models using machine learning and deep learning algorithms: Comparison models vs healthcare professionals","authors":["AH Alanazi, A Cradock, L Rainford - Radiography, 2022"],"snippet":"Introduction Referrals vetting is a necessary daily task to ensure the appropriateness of radiology referrals. Vetting requires extensive clinical knowledge and may challenge those responsible. This study aims to develop AI models to automate the …","url":["https://www.sciencedirect.com/science/article/pii/S1078817422000682"]}
+{"year":"2022","title":"Diachronic Neural Network Predictor of Word Animacy","authors":["V Bochkarev, A Achkeev, A Shevlyakova… - … International Conference on …, 2022"],"snippet":"The paper considers the problem of automatic recognition of animacy in the Russian language. We propose a recognizer that is based on the analysis of co-occurrence with the most frequent words and is trained on data from the Russian subcorpus of …","url":["https://link.springer.com/chapter/10.1007/978-3-031-19496-2_16"]}
+{"year":"2022","title":"Dialog Inpainting: Turning Documents into Dialogs","authors":["Z Dai, AT Chaganty, V Zhao, A Amini, QM Rashid… - arXiv preprint arXiv …, 2022"],"snippet":"Many important questions (eg \"How to eat healthier?\") require conversation to establish context and explore in depth. However, conversational question answering (ConvQA) systems have long been stymied by scarce training data that is expensive …","url":["https://arxiv.org/pdf/2205.09073"]}
+{"year":"2022","title":"Dictionary with the Evaluation of Positivity/Negativity Degree of the Russian Words","authors":["V Solovyev, M Islamov, V Bayrasheva - International Conference on Speech and …, 2022"],"snippet":"… It was a feed-forward neural network, with the fastText vectors of the Common Crawl model fed to its input. Significant improvement of results has been achieved: 0.870. Scores extrapolation was carried out for some other languages. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20980-2_55"]}
+{"year":"2022","title":"Did I Miss Anything? A Study on Ranking Fusion and Manual Query Rewriting in Consumer Health Search","authors":["GM Di Nunzio, F Vezzani - International Conference of the Cross-Language …, 2022"],"snippet":"In this paper, we describe the methodology and experimental analysis of a twofold strategy for the retrieval of medical relevant information: a ranking fusion and a query reformulation approach. In particular, the query reformulation approach is …","url":["https://link.springer.com/chapter/10.1007/978-3-031-13643-6_17"]}
+{"year":"2022","title":"DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings","authors":["YS Chuang, R Dangovski, H Luo, Y Zhang, S Chang… - arXiv preprint arXiv …, 2022"],"snippet":"… However, they use 1TB of the training data from Common Crawl dumps while our model only use 115MB of the Wikipedia data for pretraining. We put their scores in Table 2 for reference. In SimCSE, the authors propose to use MLM as an auxiliary …","url":["https://arxiv.org/pdf/2204.10298"]}
+{"year":"2022","title":"Differentially Private Decoding in Large Language Models","authors":["J Majmudar, C Dupuy, C Peris, S Smaili, R Gupta… - arXiv preprint arXiv …, 2022"],"snippet":"Recent large-scale natural language processing (NLP) systems use a pre-trained Large Language Model (LLM) on massive and diverse corpora as a headstart. In practice, the pre-trained model is adapted to a wide array of tasks via fine-tuning on …","url":["https://arxiv.org/pdf/2205.13621"]}
+{"year":"2022","title":"Digital artifacts reveal development and diffusion of climate research","authors":["B Carneiro, G Resce, TB Sapkota - Scientific Reports, 2022"],"snippet":"… While public web archives exist—eg WayBack Machine 48 or Common Crawl 49 —they might miss a good number of web pages, resulting in limited outcomes 50 . Building a dedicated search engine could solve the coverage issue but would …","url":["https://www.nature.com/articles/s41598-022-17717-8"]}
+{"year":"2022","title":"Dilated Convolutional Neural Networks for Lightweight Diacritics Restoration","authors":["B Csanády, A Lukács - arXiv preprint arXiv:2201.06757, 2022"],"snippet":"… In the case of HunWeb2, we used the \"2017-2018\" part of the Common Crawl subcorpus. We decided not to split up the documents to multiple chunks or sentences, as we have found that there can be a lot of repeated sentences within one document …","url":["https://arxiv.org/pdf/2201.06757"]}
+{"year":"2022","title":"DiscoSense: Commonsense Reasoning with Discourse Connectives","authors":["P Bhargava, V Ng - arXiv preprint arXiv:2210.12478, 2022"],"snippet":"We present DiscoSense, a benchmark for commonsense reasoning via understanding a wide variety of discourse connectives. We generate compelling distractors in DiscoSense using Conditional Adversarial Filtering, an extension of …","url":["https://arxiv.org/pdf/2210.12478"]}
+{"year":"2022","title":"Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation","authors":["C Wang, Y Liu, B Chen, J Zhang, W Luo, Z Huang… - arXiv preprint arXiv …, 2022"],"snippet":"End-to-end Speech Translation (ST) aims at translating the source language speech into target language text without generating the intermediate transcriptions. However, the training of end-to-end methods relies on parallel ST data, which are difficult and …","url":["https://arxiv.org/pdf/2210.09556"]}
+{"year":"2022","title":"Distillation or loss of information?: The effects of distillation on model redundancy","authors":["EE Sventickaite - 2022"],"snippet":"… The XLM-Roberta could be comparable to mBERT, as the model can process 100 languages, it was trained on 2.1 terabytes of data extracted from CommonCrawl. It is important to note, that although lacking the next sentence prediction functionality …","url":["https://www.diva-portal.org/smash/get/diva2:1681230/FULLTEXT01.pdf"]}
+{"year":"2022","title":"Distributional evidence for derivational paradigms","authors":["O Bonami, MG Naranjo - The semantics of derivational morphology. Theory …"],"snippet":"This paper provides evidence from distributional semantics on the importance of paradigmatic relations in word formation systems. We argue that, if paradigmatic relations play a systemic role, that role should be measurable by examining whether …","url":["http://www.llf.cnrs.fr/sites/llf.cnrs.fr/files/u35/MGN-OB.pdf"]}
+{"year":"2022","title":"Do children texts hold the key to commonsense knowledge?","authors":["J Romero, S Razniewski - arXiv preprint arXiv:2210.04530, 2022","S Razniewski, J Romero"],"snippet":"Compiling comprehensive repositories of commonsense knowledge is a long-standing problem in AI. Many concerns revolve around the issue of reporting bias, ie, that frequency in text sources is not a good proxy for relevance or truth. This paper …","url":["https://arxiv.org/pdf/2210.04530","https://hal.science/hal-03832361v1/file/kid_books-1.pdf"]}
+{"year":"2022","title":"Do CoNLL-2003 Named Entity Taggers Still Work Well in 2023?","authors":["S Liu, A Ritter - arXiv preprint arXiv:2212.09747, 2022"],"snippet":"… Our dataset follows this distribution to collect Reuters news articles published between December 5th and 7th, 2020, collected from the Common Crawl Foundation3. We tokenized the data with the same tokenizer used for the CoNLL-2003 corpus …","url":["https://arxiv.org/pdf/2212.09747"]}
+{"year":"2022","title":"Do Images really do the Talking?","authors":["SU Hegde, A Hande, R Priyadharshini, S Thavareesan…"],"snippet":"… The text encoder was XLM-Roberta [58], which was trained on the 100 languages Common Crawl dataset, and the image feature extraction was ResNet [59] with 152 layers, followed by linear transformation to match the word embedding size of the …","url":["https://adeeph.github.io/pdf/meme_ACI%20(1).pdf"]}
+{"year":"2022","title":"Do language models make human-like predictions about the coreferents of Italian anaphoric zero pronouns?","authors":["JA Michaelov, BK Bergen - arXiv preprint arXiv:2208.14554, 2022"],"snippet":"Some languages allow arguments to be omitted in certain contexts. Yet human language comprehenders reliably infer the intended referents of these zero pronouns, in part because they construct expectations about which referents are …","url":["https://arxiv.org/pdf/2208.14554"]}
+{"year":"2022","title":"Do We Need a Specific Corpus and Multiple High-Performance GPUs for Training the BERT Model? An Experiment on COVID-19 Dataset","authors":["N Nuntachit, P Sugunnasil - Machine Learning and Knowledge Extraction, 2022"],"snippet":"The COVID-19 pandemic has impacted daily lives around the globe. Since 2019, the amount of literature focusing on COVID-19 has risen exponentially. However, it is almost impossible for humans to read all of the studies and classify them. This article …","url":["https://www.mdpi.com/2504-4990/4/3/30/pdf?version=1656917033"]}
+{"year":"2022","title":"Document Classification with Hierarchical Graph Neural Networks","authors":["A Guille, H Attali"],"snippet":"Various neural architectures have been explored for document classification, such as convolutional and recurrent networks or as of late, Transformers. In parallel, graph neural networks have vastly improved over the recent years. In this paper, we …","url":["https://adrienguille.github.io/publications/docgat.pdf"]}
+{"year":"2022","title":"Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources","authors":["A McMillan-Major, Z Alyafeai, S Biderman, K Chen… - arXiv preprint arXiv …, 2022"],"snippet":"… Typically, this data is collected from online sources, ranging from highly edited and structured text such as Wikipedia to the myriad text and audiovisual components of web pages collected by Common Crawl1. Several issues concerning their …","url":["https://arxiv.org/pdf/2201.10066"]}
+{"year":"2022","title":"Does Corpus Quality Really Matter for Low-Resource Languages?","authors":["M Artetxe, I Aldabe, R Agerri, O Perez-de-Viñaspre… - arXiv preprint arXiv …, 2022"],"snippet":"… 2020), respectively, and were built by filtering CommonCrawl. Wikipedia has been a … Instead of filtering CommonCrawl, we do tailored crawling on 33 websites with high-quality content in … First of all, we find that, even if CommonCrawl derived …","url":["https://arxiv.org/pdf/2203.08111"]}
+{"year":"2022","title":"Domain Adaptation for Multi-Modal Foundation Models","authors":["AO Wiehe - 2022"],"snippet":"The multi-modal foundation model CLIP extracts representations of texts and images that can be used to achieve unprecedented performance in various tasks. However, this model was only trained on public data from the internet. Thus it lacks knowledge …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2022-ma-wiehe.pdf"]}
+{"year":"2022","title":"Domain Adaptation for Sparse-Data Settings: What Do We Gain by Not Using Bert?","authors":["M Sedinkina, M Schmitt, H Schütze - arXiv preprint arXiv:2203.16926, 2022"],"snippet":"The practical success of much of NLP depends on the availability of training data. However, in real-world scenarios, training data is often scarce, not least because many application domains are restricted and specific. In this work, we compare …","url":["https://arxiv.org/pdf/2203.16926"]}
+{"year":"2022","title":"Domain Adaptation of Machine Translation with Crowdworkers","authors":["M Morishita, J Suzuki, M Nagata - arXiv preprint arXiv:2210.15861, 2022"],"snippet":"… However, since CommonCrawl only covers a small portion of the web, it may overlook websites that contain valuable resources. Thus, the … In contrast, our work does not rely on CommonCrawl but on crowdworkers who can search the whole …","url":["https://arxiv.org/pdf/2210.15861"]}
+{"year":"2022","title":"Domain Adaptation of Transformer-Based Models using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback","authors":["A Idrissi-Yaghir, H Schäfer, N Bauer, CM Friedrich - arXiv preprint arXiv:2212.05764, 2022"],"snippet":"Understanding customer feedback is becoming a necessity for companies to identify problems and improve their products and services. Text classification and sentiment analysis can play a major role in analyzing this data by using a variety of machine …","url":["https://arxiv.org/pdf/2212.05764"]}
+{"year":"2022","title":"Domain Mismatch Doesn't Always Prevent Cross-Lingual Transfer Learning","authors":["D Edmiston, P Keung, NA Smith"],"snippet":"Cross-lingual transfer learning without labeled target language data or parallel text has been surprisingly effective in zero-shot cross-lingual classification, question answering, unsupervised machine translation, etc. However, some recent …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.94.pdf"]}
+{"year":"2022","title":"Domain over size: Clinical ELECTRA surpasses general BERT for bleeding site classification in the free text of electronic health records","authors":["JS Pedersen, MS Laursen, C Soguero-Ruiz… - 2022 IEEE-EMBS …, 2022"],"snippet":"Bleeding can be a life-threatening condition which occurs for 3.2% of medical patients. Information about previous bleeding and bleeding site is used to predict the risk of future bleeding and guide anticoagulant treatment. However, obtaining this …","url":["https://ieeexplore.ieee.org/abstract/document/9926955/"]}
+{"year":"2022","title":"Domain Parking: Largely Present, Rarely Considered!","authors":["J Zirngibl, S Deusch, P Sattler, J Aulbach, G Carle…"],"snippet":"… Common Crawl While visual identification allowed us to validate the inferences to a reasonable extent, we wanted to upscale validation. Therefore, we consider Common Crawl (CC) data [21] and calculate the similarity of pages. Common Crawl …","url":["https://www.net.in.tum.de/fileadmin/bibtex/publications/papers/zirngibl2022prevalenceofparking.pdf"]}
+{"year":"2022","title":"Domain-aware Multi-modality Fusion Network for Generalized Zero-shot Learning","authors":["J Wang, X Wang, H Zhang - Neurocomputing, 2022"],"snippet":"… Specifically, we investigate two word embedding methods including Word2vec[30] and Glove [36], which are trained on 1.4M Google News 2 and 2.2M Common Crawl 3 . We also consider hierarchical embeddings where similarity between objects can …","url":["https://www.sciencedirect.com/science/article/pii/S0925231222002168"]}
+{"year":"2022","title":"Domain-specific language models for multi-label classification of medical text","authors":["V Yogarajan - 2022"],"snippet":"Recent advancements in machine learning-based medical text multi-label classifications can be used to enhance the understanding of the human body and aid the need for patient care. This research considers predicting medical codes from …","url":["https://researchcommons.waikato.ac.nz/bitstream/handle/10289/14757/thesis.pdf?sequence=4&isAllowed=y"]}
+{"year":"2022","title":"Domain-Specific Machine Learning-A Human Learning Perspective","authors":["C Shan - 2022"],"snippet":"This dissertation focuses on Domain-Specific Machine Learning (DSML) with applications in the semiconductor industry. We first illustrate characteristics of DSML in view of semiconductor design and test processes, where a task is usually carried …","url":["https://escholarship.org/content/qt3m62p0hk/qt3m62p0hk.pdf"]}
+{"year":"2022","title":"Double Retrieval and Ranking for Accurate Question Answering","authors":["Z Zhang, T Vu, A Moschitti - arXiv preprint arXiv:2201.05981, 2022"],"snippet":"… Then, we used it to build a large index having up to 130MM passages extracted from 54MM documents of CommonCrawl2. We selected English Web documents of 5,000 most popular domains, including Wikipedia, from the recent releases of …","url":["https://arxiv.org/pdf/2201.05981"]}
+{"year":"2022","title":"DS4DH at TREC Health Misinformation 2021: Multi-Dimensional Ranking Models with Transfer Learning and Rank Fusion","authors":["B Zhang, N Naderi, F Jaume-Santero, D Teodoro - arXiv preprint arXiv:2202.06771, 2022"],"snippet":"This paper describes the work of the Data Science for Digital Health (DS4DH) group at the TREC Health Misinformation Track 2021. The TREC Health Misinformation track focused on the development of retrieval methods that provide relevant, correct …","url":["https://arxiv.org/pdf/2202.06771"]}
+{"year":"2022","title":"Dutch SQuAD and Ensemble Learning for Question Answering from Labour Agreements","authors":["NJ Rouws, S Vakulenko, S Katrenko - Benelux Conference on Artificial Intelligence, 2021"],"snippet":"The Dutch Ministry of Social Affairs and Employment has to regularly explore the content of labour agreements. Studies on topics such as diversity and work flexibility are conducted on the regular basis by means of specialised questionnaires. We …","url":["https://link.springer.com/chapter/10.1007/978-3-030-93842-0_9"]}
+{"year":"2022","title":"Early depression detection in social media based on deep learning and underlying emotions","authors":["JSL Figuerêdo, ALLM Maia, RT Calumby - Online Social Networks and Media, 2022"],"snippet":"Depression is a challenge to public health, frequently related to disability and one of the reasons that lead to suicide. Many of the ones who suffer depression use social media to obtain information or even to talk about their problem. Some studies have …","url":["https://www.sciencedirect.com/science/article/pii/S2468696422000283"]}
+{"year":"2022","title":"Early risk detection of mental illnesses using various types of textual features","authors":["R Ferreira, A Trifan, JL Oliveira - Working Notes of CLEF, 2022"],"snippet":"This paper documents the participation of our team, BioInfo@ UAVR, in the first and second task of the 2022 edition of CLEF eRisk. With the goal of achieving an early detection of subjects at risk of specific mental illnesses, pathological gambling and …","url":["http://ceur-ws.org/Vol-3180/paper-72.pdf"]}
+{"year":"2022","title":"EDIN: An End-to-end Benchmark and Pipeline for Unknown Entity Discovery and Indexing","authors":["N Kassner, F Petroni, M Plekhanov, S Riedel… - arXiv preprint arXiv …, 2022"],"snippet":"Existing work on Entity Linking mostly assumes that the reference knowledge base is complete, and therefore all mentions can be linked. In practice this is hardly ever the case, as knowledge bases are incomplete and because novel concepts arise …","url":["https://arxiv.org/pdf/2205.12570"]}
+{"year":"2022","title":"Effective Approaches to Neural Query Language Identification","authors":["X Ren, B Yang, D Liu, H Zhang, X Lv, L Yao, J Xie - Computational Linguistics, 2022"],"snippet":"… Commoncow: Massively huge web corpora from commoncrawl data and a method to distribute them freely under restrictive EU copyright laws. In Proceedings of the Tenth International Conference on Language Resources and Evaluation …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00451/2035281/coli_a_00451.pdf"]}
+{"year":"2022","title":"Effective Transfer Learning for Low-Resource Natural Language Understanding","authors":["Z Liu - arXiv preprint arXiv:2208.09180, 2022"],"snippet":"Natural language understanding (NLU) is the task of semantic decoding of human languages by machines. NLU models rely heavily on large training data to ensure good performance. However, substantial languages and domains have very few …","url":["https://arxiv.org/pdf/2208.09180"]}
+{"year":"2022","title":"Effectiveness of French Language Models on Abstractive Dialogue Summarization Task","authors":["Y Zhou, F Portet, F Ringeval - arXiv preprint arXiv:2207.08305, 2022"],"snippet":"Pre-trained language models have established the state-of-the-art on various natural language processing tasks, including dialogue summarization, which allows the reader to quickly access key information from long conversations in meetings …","url":["https://arxiv.org/pdf/2207.08305"]}
+{"year":"2022","title":"Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasks","authors":["E Villatoro-Tello, S Madikeri, J Zuluaga-Gomez… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper, we perform an exhaustive evaluation of different representations to address the intent classification problem in a Spoken Language Understanding (SLU) setup. We benchmark three types of systems to perform the SLU intent detection task …","url":["https://arxiv.org/pdf/2212.08489"]}
+{"year":"2022","title":"Effects of Physiological Signals in Different Types of Multimodal Sentiment Estimation","authors":["S Katada, S Okada, K Komatani - IEEE Transactions on Affective Computing, 2022"],"snippet":"… FastText word vectors FastText is a recently developed language model for training word vectors with subword information on Wikipedia and the Common Crawl corpus [41]. This language model is not restricted to English and is available …","url":["https://ieeexplore.ieee.org/abstract/document/9726810/"]}
+{"year":"2022","title":"Effects of Similarity Score Functions in Attention Mechanisms on the Performance of Neural Question Answering Systems","authors":["Y Shen, EMK Lai, M Mohaghegh - Neural Processing Letters, 2022"],"snippet":"Attention mechanisms have been incorporated into many neural network-based natural language processing (NLP) models. They enhance the ability of these models to learn and reason with long input texts. A critical part of such mechanisms …","url":["https://link.springer.com/article/10.1007/s11063-021-10730-4"]}
+{"year":"2022","title":"Efficient and Accurate Closed-Domain and Open-Domain Long-Form Question Answering","authors":["RS Butler, VD Duggirala, F Banaei-Kashani - International Conference on Computer …, 2022"],"snippet":"We present an efficient and accurate long-form question answering platform, dubbed iLFQA (ie, short for intelligent Long-Form Question Answering). iLFQA was created as a continuation of iTA (ie, short for intelligent Teaching Assistant). iTA was …","url":["https://link.springer.com/chapter/10.1007/978-3-031-14756-2_9"]}
+{"year":"2022","title":"Efficient Language Modeling with Sparse all-MLP","authors":["P Yu, M Artetxe, M Ott, S Shleifer, H Gong, V Stoyanov… - arXiv preprint arXiv …, 2022"],"snippet":"All-MLP architectures have attracted increasing interest as an alternative to attention-based models. In NLP, recent work like gMLP shows that all-MLPs can match Transformers in language modeling, but still lag behind in downstream tasks. In this work, we …","url":["https://arxiv.org/pdf/2203.06850"]}
+{"year":"2022","title":"Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss","authors":["Y Lee, KT Lim, W Baek, B Roh, S Kim - … of the 29th International Conference on …, 2022"],"snippet":"… Image-text pairs We follow the data collection process of ALIGN to create our in-house 1B imagetext pairs dataset from Common crawl 2. The raw descriptions are gathered from the Alt-text HTML attribute associated with web images. We only apply …","url":["https://aclanthology.org/2022.coling-1.504.pdf"]}
+{"year":"2022","title":"Effortless and beneficial processing of natural languages using transformers","authors":["K Amrutha, P Prabu - Journal of Discrete Mathematical Sciences and …, 2022"],"snippet":"Natural Language Processing plays a vital role in our day-to-day life. Deep learning models for NLP help make human life easier as computers can think, talk, and interact like humans. Applications of the NLP models can be seen in many domains …","url":["https://www.tandfonline.com/doi/abs/10.1080/09720529.2022.2133239"]}
+{"year":"2022","title":"ELF22: A Context-based Counter Trolling Dataset to Combat Internet Trolls","authors":["H Lee, YJ NA, H Song, J Shin, JC Park"],"snippet":"Online trolls increase social costs and cause psychological damage to individuals. With the proliferation of automated accounts making use of bots for trolling, it is difficult for targeted individual users to handle the situation both quantitatively and …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.378.pdf"]}
+{"year":"2022","title":"Elite Environmental Aesthetics: Placing Nature in a Changing Climate","authors":["A McCumber, A Davis - American Journal of Cultural Sociology, 2022"],"snippet":"What does it mean to escape to nature in a changing climate? We investigate the properties that make a place resonant with ideas of “nature,” particularly for liberal elite vacationers consuming place through travel. By analyzing over 10,000 articles …","url":["https://link.springer.com/article/10.1057/s41290-022-00179-w"]}
+{"year":"2022","title":"ElitePLM: An Empirical Study on General Language Ability Evaluation of Pretrained Language Models","authors":["J Li, T Tang, Z Gong, L Yang, Z Yu, Z Chen, J Wang… - arXiv preprint arXiv …, 2022"],"snippet":"Nowadays, pretrained language models (PLMs) have dominated the majority of NLP tasks. While, little research has been conducted on systematically evaluating the language abilities of PLMs. In this paper, we present a large-scale empirical study …","url":["https://arxiv.org/pdf/2205.01523"]}
+{"year":"2022","title":"Emerging trends: General fine-tuning (gft)","authors":["KW Church, X Cai, Y Ying, Z Chen, G Xun, Y Bian - Natural Language Engineering, 2022"],"snippet":"This paper describes gft (general fine-tuning), a little language for deep nets, introduced at an ACL-2022 tutorial. gft makes deep nets accessible to a broad audience including non-programmers. It is standard practice in many fields to use …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/909A753B5EC40310A8DC2A3093CAE9F6/S1351324922000237a.pdf/emerging-trends-general-fine-tuning-gft.pdf"]}
+{"year":"2022","title":"Emerging Trends: SOTA-Chasing","authors":["KW Church, V Kordoni - Natural Language Engineering, 2022"],"snippet":"Many papers are chasing state-of-the-art (SOTA) numbers, and more will do so in the future. SOTA-chasing comes with many costs. SOTA-chasing squeezes out more promising opportunities such as coopetition and interdisciplinary collaboration. In …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/5E9F9F796159040973053C52C443C1D6/S1351324922000043a.pdf/emerging_trends_sotachasing.pdf"]}
+{"year":"2022","title":"Emotion Classification of MIDI Lyrics Using Transformers","authors":["PMP de Oliveira - 2022"],"snippet":"… It uses the common crawl web extracted text [34] as a dataset for pre-training, where after some data cleaning and filtering, it ends up with 750GB of uncompressed English text, way more than RoBERTa, which was already an …","url":["https://repositorio-aberto.up.pt/bitstream/10216/142445/2/570765.pdf"]}
+{"year":"2022","title":"Emotion Detection using Deep Learning","authors":["Y Shaaban, H Korashy, W Medhat - 2021 16th International Conference on Computer …, 2021"],"snippet":"Emotion detection is one of the challenging tasks in Natural Language Processing. The applications of emotion detection can be utilized in different fields like data mining, psychology, and human-computer interaction. The paper aims to train …","url":["https://ieeexplore.ieee.org/abstract/document/9686108/"]}
+{"year":"2022","title":"Emotion-Aware Multimodal Pre-training for Image-Grounded Emotional Response Generation","authors":["Z Tian, Z Wen, Z Wu, Y Song, J Tang, D Li, NL Zhang - International Conference on …, 2022"],"snippet":"Face-to-face communication leads to better interactions between speakers than text-to-text conversations since the speakers can capture both textual and visual signals. Image-grounded emotional response generation (IgERG) tasks requires chatbots to generate a …","url":["https://link.springer.com/chapter/10.1007/978-3-031-00129-1_1"]}
+{"year":"2022","title":"Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey","authors":["K Nozawa, I Sato - arXiv preprint arXiv:2204.08226, 2022"],"snippet":"Representation learning enables us to automatically extract generic feature representations from a dataset to solve another machine learning task. Recently, extracted feature representations by a representation learning algorithm and a …","url":["https://arxiv.org/pdf/2204.08226"]}
+{"year":"2022","title":"Employing a Multilingual Transformer Model for Segmenting Unpunctuated Arabic Text","authors":["AM Alshanqiti, S Albouq, AB Alkhodre, A Namoun… - 2022"],"snippet":"Long unpunctuated texts containing complex linguistic sentences are a stumbling block to processing any low-resource languages. Thus, approaches that attempt to segment lengthy texts with no proper punctuation into simple candidate sentences …","url":["https://www.preprints.org/manuscript/202208.0451/download/final_file"]}
+{"year":"2022","title":"En-SeqGAN: An Efficient Sequence Generation Model for Deceiving URL Classifiers","authors":["TD Pham, TTT Pham, VC Ta - Asian Conference on Intelligent Information and …, 2022"],"snippet":"… The URLs in the data are crawled from Common Crawl website [19] and Phishtank [20] It resulted in 6 million legitimate URLs from Common Crawl and 1 million phish URLs from Phishtank. We follow the preprocessing procedure from [21] …","url":["https://link.springer.com/chapter/10.1007/978-981-19-8234-7_37"]}
+{"year":"2022","title":"Energy-Efficient Data Transfer Optimization via Decision-Tree Based Uncertainty Reduction","authors":["H Jamil, L Rodolph, J Goldverg, T Kosar - arXiv preprint arXiv:2204.07601, 2022"],"snippet":"… These include: (1) the small file size dataset consisting of 20,000 HTML files derived from the common crawl project [24]; (2) the medium file size dataset consisting of 5,000 image files derived from Flickr [25]; (3) the large file size dataset …","url":["https://arxiv.org/pdf/2204.07601"]}
+{"year":"2022","title":"Enhanced Distance-aware Self-attention and Multi-level Match for Sentence Semantic Matching","authors":["Y Deng, X Li, M Zhang, X Lu, X Sun - Neurocomputing, 2022"],"snippet":"Sentence semantic matching is a core research area in natural language processing, which is widely used in various natural language tasks. In recent years, attention mechanism has shown good performance in deep neural networks for sentence …","url":["https://www.sciencedirect.com/science/article/pii/S0925231222006877"]}
+{"year":"2022","title":"Enhancing Cross-lingual Prompting with Mask Token Augmentation","authors":["M Zhou, X Li, Y Jiang, L Bing - arXiv preprint arXiv:2202.07255, 2022"],"snippet":"… Model Details XLM-R base model, containing 270M parameters, is pretrained on 2.5TB of filtered CommonCrawl on 100 languages. It contains 12 Transformer layers with hidden space dimensions of 768 and 12 attention heads in each layer. …","url":["https://arxiv.org/pdf/2202.07255"]}
+{"year":"2022","title":"Enhancing Indic Handwritten Text Recognition Using Global Semantic Information","authors":["A Mondal, CV Jawahar - International Conference on Frontiers in Handwriting …, 2022"],"snippet":"Handwritten Text Recognition (htr) is more interesting and challenging than printed text due to uneven variations in the handwriting style of the writers, content, and time. htr becomes more challenging for the Indic languages because of (i) multiple …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21648-0_25"]}
+{"year":"2022","title":"Enhancing Mobile App Bug Reporting via Real-time Understanding of Reproduction Steps","authors":["M Fazzini, K Moran, CB Cardenas, T Wendland, A Orso… - arXiv preprint arXiv …, 2022"],"snippet":"… The module uses the FastText model trained on the Common Crawl dataset [39] to identify the semantic similarity between S2R descriptions and GUI element properties. The web application also provides access to bug reports saved in a …","url":["https://arxiv.org/pdf/2203.12093"]}
+{"year":"2022","title":"Enhancing the Performance of Text Mining","authors":["FM Al Shanik - 2021"],"snippet":"The amount of text data produced in science, finance, social media, and medicine is growing at an unprecedented pace. The raw text data typically introduces major computational and analytical obstacles (eg, extremely high dimensionality) to data …","url":["https://tigerprints.clemson.edu/cgi/viewcontent.cgi?article=3929&context=all_dissertations"]}
+{"year":"2022","title":"Enhancing Vietnamese Question Generation with Reinforcement Learning","authors":["N Vu, K Van Nguyen - Asian Conference on Intelligent Information and …, 2022"],"snippet":"Along with automatic question answering and machine reading comprehension, question generation has become a popular yet challenging task of natural language understanding in recent years. However, as far as we are concerned, there was no …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21743-2_45"]}
+{"year":"2022","title":"Enriching Grammatical Error Correction Resources for Modern Greek","authors":["K Korre, J Pavlopoulos"],"snippet":"… T5 was pre-trained on 750GB of Englishlanguage text that was sourced from the public Common Crawl web.MT5 was pre-trained on data from all of the 71 monthly web scrapes released so far by Common Crawl, which is more than the source data …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.532.pdf"]}
+{"year":"2022","title":"Ensembling of Various Transformer Based Models for the Fake News Detection Task in the Urdu Language","authors":["S Kalraa, P Vermaa, Y Sharmaa, GS Chauhanb"],"snippet":"The spread of misinformation has become a severe issue affecting society. Inaccurate information has enormous potential to cause real-world impacts. Developing algorithms to detect fake news automatically will be very useful in …","url":["http://ceur-ws.org/Vol-3159/T7-10.pdf"]}
+{"year":"2022","title":"Entity-Assisted Language Models for Identifying Check-worthy Sentences","authors":["T Su, C Macdonald, I Ounis - arXiv preprint arXiv:2211.10678, 2022"],"snippet":"We propose a new uniform framework for text classification and ranking that can automate the process of identifying check-worthy sentences in political debates and speech transcripts. Our framework combines the semantic analysis of the sentences …","url":["https://arxiv.org/pdf/2211.10678"]}
+{"year":"2022","title":"Entry and Acquisitions in Software Markets","authors":["L Eisfeld - 2022"],"snippet":"How do acquisitions of young, innovative, venture capital funded firms (startups) affect entry incentives of new firms? I create a new dataset by merging web-scraped product-level data on enterprise software with data on firms’ entry and acquisition …","url":["https://luiseeisfeld.github.io/assets/docs/JMP_Eisfeld_TSE.pdf"]}
+{"year":"2022","title":"Epidemic Question Answering: question generation and entailment for Answer Nugget discovery","authors":["MA Weinzierl, SM Harabagiu - Journal of the American Medical Informatics …, 2022"],"snippet":"Objective The rapidly growing body of communications during the COVID-19 pandemic posed a challenge to information seekers, who struggled to find answers to their specific and changing information needs. We designed a Question …","url":["https://academic.oup.com/jamia/advance-article-abstract/doi/10.1093/jamia/ocac222/6832056"]}
+{"year":"2022","title":"Equivocal URLs: Understanding the Fragmented Space of URL Parser Implementations","authors":["J Reynolds, A Bates, M Bailey - European Symposium on Research in Computer …, 2022"],"snippet":"Uniform Resource Locators (URLs) are integral to the Web and have existed for nearly three decades. Yet URL parsing differs subtly among parser implementations, leading to ambiguity that can be abused by attackers. We measure agreement …","url":["https://link.springer.com/chapter/10.1007/978-3-031-17143-7_9"]}
+{"year":"2022","title":"ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages","authors":["Y Chai, S Wang, C Pang, Y Sun, H Tian, H Wu - arXiv preprint arXiv:2212.06742, 2022"],"snippet":"… 25 languages from CommonCrawl. It learns to reconstruct the full NL texts from corrupted ones with an arbitrary noising function. mT5 (Xue et al., 2021) is a multilingual-NL encoder-decoder model adapted from T5. It is trained on 101 NLs …","url":["https://arxiv.org/pdf/2212.06742"]}
+{"year":"2022","title":"esCorpius: A Massive Spanish Crawling Corpus","authors":["A Gutiérrez-Fandiño, D Pérez-Fernández… - arXiv e-prints, 2022"],"snippet":"… In this paper, we introduce esCorpius, a Spanish crawling corpus obtained from near 1 Pb of Common Crawl data. It is the most extensive corpus in Spanish with this level of quality in the extraction, purification and deduplication of web textual content …","url":["https://ui.adsabs.harvard.edu/abs/2022arXiv220615147G/abstract"]}
+{"year":"2022","title":"Estimating Confidence of Predictions of Individual Classifiers and Their Ensembles for the Genre Classification Task","authors":["M Lepekhin, S Sharoff"],"snippet":"… It has a similar architecture but uses a bigger and more genre-diverse corpus based on Common Crawl (instead of Wikipedia for the multilingual BERT). Therefore, we choose XLM-RoBERTa as the classifier for the experiments in our research. One …","url":["http://corpus.leeds.ac.uk/serge/publications/2022-LREC-genre.pdf"]}
+{"year":"2022","title":"Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review","authors":["GO Adebayo, RV Yampolskiy - Big Data Mining and Analytics, 2022"],"snippet":"… the curve of the collegiate word ratio (CWR) — the ratio of the total count of collegiate words (words SAT consider a part of strong vocabulary usage) used in a written text to the total count of words in the text, of sample texts with more than 100 …","url":["https://ieeexplore.ieee.org/iel7/8254253/9793354/09793359.pdf"]}
+{"year":"2022","title":"Estimating time-series changes in social sentiment@ Twitter in US metropolises during the COVID-19 pandemic","authors":["R Saito, S Haruyama - Journal of Computational Social Science, 2022"],"snippet":"Since early 2020, the global coronavirus pandemic has strained economic activities and traditional lifestyles. For such emergencies, our paper proposes a social sentiment estimation model that changes in response to infection conditions and …","url":["https://link.springer.com/article/10.1007/s42001-022-00186-4"]}
+{"year":"2022","title":"Estimation on the Importance of Semantic Web Integration for Art and Culture Related Online Media Outlets","authors":["A Giannakoulopoulos, M Pergantis, N Konstantinou… - Future Internet, 2022"],"snippet":"… Such a list was acquired through Common Crawl a “non-profit organization dedicated to … This process, which was developed in PHP, used Common Crawl’s API to receive a list of domains … The language of a website was identified based …","url":["https://www.mdpi.com/1999-5903/14/2/36/pdf"]}
+{"year":"2022","title":"Estonian Language Understanding: a Case Study on the COPA Task","authors":["HA KUULMETS, A TATTAR, M FISHEL"],"snippet":"The lack of Estonian NLU datasets severely affects advancing Estonian-specific NLP research. With this paper we aim to relieve the issue by publishing a new Estonian NLU dataset EstCOPA. We benchmark the task on several Estonian and multilingual …","url":["https://www.bjmc.lu.lv/fileadmin/user_upload/lu_portal/projekti/bjmc/Contents/10_3_19_Kuulmets.pdf"]}
+{"year":"2022","title":"Ethnic Bias in Judicial Decision-making: Evidence from Criminal Appeals in Kenya","authors":["DD Choi, JA Harris, F Shen-Bayh"],"snippet":"… ), we used the Common Crawl GLoVe model that was trained using a . million word vocabulary. Rodriguez and Spirling (Nd) further nd that pretrained word vectors perform well against both locally trained vectors and human coders. …","url":["https://www.dhdannychoi.com/files/CHS_EthnicBias.pdf"]}
+{"year":"2022","title":"eTranslation's Submissions to the WMT22 General Machine Translation Task","authors":["C Oravecz, K Bontcheva, D Kolovratník, B Kovachev…"],"snippet":"The paper describes the 3 NMT models submitted by the eTranslation team to the WMT22 general machine translation shared task. In the WMT news task last year, multilingual systems with deep and complex architectures utilizing immense …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.29.pdf"]}
+{"year":"2022","title":"EtriCA: Event-Triggered Context-Aware Story Generation Augmented by Cross Attention","authors":["C Tang, C Lin, H Huang, F Guerin, Z Zhang - arXiv preprint arXiv:2210.12463, 2022"],"snippet":"One of the key challenges of automatic story generation is how to generate a long narrative that can maintain fluency, relevance, and coherence. Despite recent progress, current story generation systems still face the challenge of how to …","url":["https://arxiv.org/pdf/2210.12463"]}
+{"year":"2022","title":"European Language Equality-Report on the French Language","authors":["G Adda, A Braffort, I Vasilescu, F Yvon - 2022"],"snippet":"This report presents a survey of the current state of technologies for the automatic processing of the French language as well as French Sign Language (FSL). Similar reports have been prepared independently for all languages of the European Union …","url":["https://hal.archives-ouvertes.fr/hal-03637776/document"]}
+{"year":"2022","title":"Evaluate and Visualize Legal Embeddings for Explanation Purpose","authors":["NH Thanh, DT Binh, BM Quan, N Le Minh - 2021 13th International Conference on …, 2021"],"snippet":"Deep learning models have recently demonstrated promising results on legal-related tasks. However, the performance of the models is not enough for us to have a clear understanding of their behavior and the reason for such performance. This paper is …","url":["https://ieeexplore.ieee.org/abstract/document/9648655/"]}
+{"year":"2022","title":"Evaluate Similarity of Requirements with Multilingual Natural Language Processing","authors":["U Bisang, J Brünnhäußer, P Lünnemann, L Kirsch… - Proceedings of the Design …, 2022"],"snippet":"Finding redundant requirements or semantically similar ones in previous projects is a very time-consuming task in engineering design, especially with multilingual data. Due to modern NLP it is possible to automate such tasks. In this paper we compared …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/2733FA14767D66DEE559E39594732BDD/S2732527X22001535a.pdf/div-class-title-evaluate-similarity-of-requirements-with-multilingual-natural-language-processing-div.pdf"]}
+{"year":"2022","title":"Evaluating Computational Models of Similarity against a Human Rated Dataset","authors":["E BARBU, VB MITITELU"],"snippet":"… The English distributional models were trained on Wikipedia and on the Common Crawl corpus containing English text. The semantic … a language identifier from Common Crawl and Wikipedia. The model is trained with a vector size of 100 …","url":["https://www.bjmc.lu.lv/fileadmin/user_upload/lu_portal/projekti/bjmc/Contents/10_3_03_Barbu1.pdf"]}
+{"year":"2022","title":"Evaluating Pre-Trained Transformers on Italian Administrative Texts","authors":["S Auriemma, M Miliani, A Bondielli, LC Passaro… - 2022"],"snippet":"In recent years, Transformer-based models have been widely used in NLP for various downstream tasks and in different domains. However, a language model explicitly built for the Italian administrative language is still lacking. Therefore, in this …","url":["https://ceur-ws.org/Vol-3285/paper4.pdf"]}
+{"year":"2022","title":"Evaluating Pre-training Objectives for Low-Resource Translation into Morphologically Rich Languages","authors":["P Dhar, A Bisazza, G van Noord"],"snippet":"The scarcity of parallel data is a major limitation for Neural Machine Translation (NMT) systems, in particular for translation into morphologically rich languages (MRLs). An important way to overcome the lack of parallel data is to leverage target monolingual …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.527.pdf"]}
+{"year":"2022","title":"Evaluating the Construct Validity of Text Embeddings with Application to Survey Questions","authors":["Q Fang, D Nguyen, DL Oberski - arXiv preprint arXiv:2202.09166, 2022"],"snippet":"Text embedding models from Natural Language Processing can map text data (eg words, sentences, documents) to supposedly meaningful numerical representations (aka text embeddings). While such models are increasingly applied in social science …","url":["https://arxiv.org/pdf/2202.09166"]}
+{"year":"2022","title":"Evaluating the Impact of OCR Quality on Short Texts Classification Task","authors":["O Vitman, Y Kostiuk, P Plachinda, A Zhila, G Sidorov… - … International Conference on …, 2022"],"snippet":"… As those embeddings have been trained on different kinds of text corpora ranging from Wikipedia to CommonCrawl Corpus Footnote 7 , they … On the other hand, Common Crawl Corpus is a huge corpus of a large chunk of the Internet, and the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-19496-2_13"]}
+{"year":"2022","title":"Evaluating Topic Modeling Pre-processing Pipelines for Portuguese Texts","authors":["APDS Júnior, P Cecilio, F Viegas, W Cunha… - Brazilian Symposium on …, 2022"],"snippet":"… De acordo com [31], os autores utilizam os vetores pré-treinados do FastText – modelo pré-treinado a partir do corpus Common Crawl. Dessa forma, adaptamos as CluWords para representação de textos em português utilizando os vetores …","url":["https://dl.acm.org/doi/abs/10.1145/3539637.3557052"]}
+{"year":"2022","title":"Evaluating transfer learning approach for detecting Arabic anti-refugee/migrant speech on social media","authors":["D Mohdeb, M Laifa, F Zerargui, O Benzaoui - Aslib Journal of Information …, 2022"],"snippet":"Purpose The present study was designed to investigate eight research questions that are related to the analysis and the detection of dialectal Arabic hate speech that targeted African refugees and illegal migrants on the YouTube Algerian space …","url":["https://www.emerald.com/insight/content/doi/10.1108/AJIM-10-2021-0293/full/html"]}
+{"year":"2022","title":"Evaluation and Analysis of the NLP Model Zoo for Ukrainian Text Classification","authors":["D Panchenko, D Maksymenko, O Turuta, A Yerokhin… - International Conference on …, 2022"],"snippet":"One of the crucial problems of natural language processing for languages such as Ukrainian is lack of datasets both unlabeled (for pretraining of word embeddings or large deep learning models) and labeled (for benchmarking existing approaches). In …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20834-8_6"]}
+{"year":"2022","title":"Evaluation Methods for Representation Learning: A Survey","authors":["K Nozawa, I Sato - IJCAI-ECAI Survey Track, 2022"],"snippet":"Abstract Representation learning enables us to automatically extract generic feature representations from a dataset to solve another machine learning task. Recently, extracted feature representations by a representation learning algorithm and a …","url":["https://www.ijcai.org/proceedings/2022/0776.pdf"]}
+{"year":"2022","title":"Evaluation of an automated Presidio anonymisation model for unstructured radiation oncology electronic medical records in an Australian setting","authors":["DP Kotevsk, RI Smee, M Field, YN Nemes, K Broadley… - International Journal of …, 2022"],"snippet":"Background Electronic medical records (EMRs) contain valuable information for clinical research, however, the presence of personally identifying information (PII) restricts their use. Anonymisation of PII from EMRs enables clinical information to be …","url":["https://www.sciencedirect.com/science/article/pii/S1386505622001940"]}
+{"year":"2022","title":"Evaluation of Transfer Learning for Polish with a Text-to-Text Model","authors":["A Chrabrowa, Ł Dragan, K Grzegorczyk, D Kajtoch… - arXiv preprint arXiv …, 2022"],"snippet":"We introduce a new benchmark for assessing the quality of text-to-text models for Polish. The benchmark consists of diverse tasks and datasets: KLEJ benchmark adapted for text-to-text, en-pl translation, summarization, and question answering. In …","url":["https://arxiv.org/pdf/2205.08808"]}
+{"year":"2022","title":"Evaluation of Word Embedding Models in Latvian NLP Tasks Based on Publicly Available Corpora","authors":["R Laucis, G Jēkabsons - Applied Computer Systems, 2021"],"snippet":"Nowadays, natural language processing (NLP) is increasingly relaying on pre-trained word embeddings for use in various tasks. However, there is little research devoted to Latvian–a language that is much more morphologically complex than English. In …","url":["https://sciendo.com/pdf/10.2478/acss-2021-0016"]}
+{"year":"2022","title":"Event prediction from news text using subgraph embedding and graph sequence mining","authors":["RF Cekinel, P Karagoz - World Wide Web, 2022"],"snippet":"Event detection from textual content by using text mining concepts is a well-researched field in the literature. On the other hand, graph modeling and graph embedding techniques in recent years provide an opportunity to represent textual contents as …","url":["https://link.springer.com/article/10.1007/s11280-021-01002-1"]}
+{"year":"2022","title":"Expanding Knowledge Graphs with Humans in the Loop","authors":["E Manzoor, J Tong, S Vijayaraghavan, R Li - arXiv preprint arXiv:2212.05189, 2022"],"snippet":"… The PinText embeddings are trained on millions of tokens from the Pinterest platform8, whereas the FastText embeddings are trained on 6.3 billion tokens from the Common Crawl website archive. Thus, the two embedding approaches have …","url":["https://arxiv.org/pdf/2212.05189"]}
+{"year":"2022","title":"Experimental Comparison of Ansätze for Quantum Natural Language Processing","authors":["N Khatri"],"snippet":"The DisCoCat model of natural language is a framework which serves as the foundation for several contemporary experiments in Quantum Natural Language Processing (QNLP). In this model, sentences are represented as string diagrams …","url":["http://www.cs.ox.ac.uk/people/aleks.kissinger/theses/khatri-thesis.pdf"]}
+{"year":"2022","title":"Experimental Study on Backwash of Tsunami Acting on Caisson-Type Quay Wall","authors":["CTQ Wall"],"snippet":"Documents in HENRY are made available under the Creative Commons License CC BY 4.0, if no other license is applicable. Under CC BY 4.0 commercial use and sharing, remixing, transforming, and building upon the material of the work is …","url":["https://9dok.net/document/dzxor4oz-experimental-study-backwash-tsunami-acting-caisson-type-quay.html"]}
+{"year":"2022","title":"Explainable detection of adverse drug reaction with imbalanced data distribution","authors":["J Wang, LC Yu, X Zhang - PLOS Computational Biology, 2022"],"snippet":"… For BiLSTM, the word vectors were pre-trained using GloVe on the 840B Common Crawl corpus [28]. The dimensionality of the word vectors is 300. Words that don’t appear in GloVe were initialized with a uniform distribution U(−0.25, 0.25). …","url":["https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010144"]}
+{"year":"2022","title":"Exploiting Document-based Features for Clarification in Conversational Search","authors":["I Sekulić, M Aliannejadi, F Crestani - European Conference on Information Retrieval, 2022"],"snippet":"… For that purpose, we utilise Chatnoir [7] – a freely accessible Elasticsearch-based search engine with indexes of ClueWeb and CommonCrawl … Elastic ChatNoir: search engine for the ClueWeb and the common crawl. In: Pasi, G., Piwowarski, B …","url":["https://link.springer.com/chapter/10.1007/978-3-030-99736-6_28"]}
+{"year":"2022","title":"Exploiting Ensemble of Transformer Models for Detecting Informative Tweets","authors":["AN Chowdhury, S Guha, N Amin, SI Khan - 2021 IEEE 18th India Council …, 2021"],"snippet":"Microblogging platforms especially Twitter is considered as one of the prominent medium of getting user-generated information. Millions of tweets were posted daily during COVID-19 pandemic days and the rate increases gradually. Tweets include a …","url":["https://ieeexplore.ieee.org/abstract/document/9691734/"]}
+{"year":"2022","title":"Exploiting Linguistic Information from Nepali Transcripts for Early Detection of Alzheimer's Disease using the State-of-the-art Techniques of Machine Learning and …","authors":["S Adhikari, S Thapa, U Naseem, P Singh, A Huo…"],"snippet":"… Similarly, for the pre-trained fastText embeddings, the pre-trained word vectors trained on Common Crawl and Wikipedia using fastText were used [39]. The model was trained by using CBOW with position-weights, in dimension 300, with character …","url":["https://www.researchgate.net/profile/Surendrabikram-Thapa/publication/357190395_Exploiting_Linguistic_Information_from_Nepali_Transcripts_for_Early_Detection_of_Alzheimer's_Disease_using_Natural_Language_Processing_and_Machine_Learning_Techniques/links/6380f5107b0e356feb823970/Exploiting-Linguistic-Information-from-Nepali-Transcripts-for-Early-Detection-of-Alzheimers-Disease-using-Natural-Language-Processing-and-Machine-Learning-Techniques.pdf"]}
+{"year":"2022","title":"Exploration of text features representation on applications to the insurance domain","authors":["M Garcia Ribes - 2022"],"snippet":"The recent popularization of a more data-centric paradigm in machine learning has turned the study of the quality of feature representation into a very relevant topic. In this document an exploration of different text features representation applied to a …","url":["https://upcommons.upc.edu/bitstream/handle/2117/363257/165184.pdf?sequence=1"]}
+{"year":"2022","title":"Exploring Automatic Text Simplification of Requirements","authors":["EG Guren - 2022"],"snippet":"… The mined paraphrases are sequences of words with the same meaning extracted from a large collection of texts from Common Crawl7, an open-source collection of web crawl data. The system simplifies text by using the mined …","url":["https://www.duo.uio.no/bitstream/handle/10852/95635/8/thesis_final.pdf"]}
+{"year":"2022","title":"Exploring Capabilities of Monolingual Audio Transformers using Large Datasets in Automatic Speech Recognition of Czech","authors":["J Lehečka, J Švec, A Pražák, JV Psutka - arXiv preprint arXiv:2206.07627, 2022"],"snippet":"… is a huge collection of cleaned and deduplicated web pages from Common Crawl project4. Since this text corpus contains almost 13 billion … • adding LM into the beam search CTC decoder; we found the Common Crawl project to be a useful …","url":["https://arxiv.org/pdf/2206.07627"]}
+{"year":"2022","title":"Exploring Dimensionality Reduction Techniques in Multilingual Transformers","authors":["Á Huertas-García, A Martín, J Huertas-Tato… - arXiv preprint arXiv …, 2022"],"snippet":"Both in scientific literature and in industry,, Semantic and context-aware Natural Language Processing-based solutions have been gaining importance in recent years. The possibilities and performance shown by these models when dealing with …","url":["https://arxiv.org/pdf/2204.08415"]}
+{"year":"2022","title":"Exploring Models for Automatic Keyword Labelling of Scientific Documents","authors":["J Gabín, ME Ares, J Parapar - 2022"],"snippet":"Automatic keyword labelling methods generate a set of short phrases for a given document providing a short and good description of its content. Those labels are critical in tasks such as exploratory search and for improving the information …","url":["http://ceur-ws.org/Vol-3178/CIRCLE_2022_paper_04.pdf"]}
+{"year":"2022","title":"Exploring Swedish & English fastText Embeddings","authors":["T Adewumi, F Liwicki, M Liwicki"],"snippet":"In this paper, we show that embeddings from relatively smaller corpora sometimes outperform those from larger corpora and we introduce a new Swedish analogy test set and make it publicly available. To achieve good performance in Natural …","url":["https://aic20.aass.oru.se/aic-pdfs/AIC-2022-camera-ready-short-paper-07.pdf"]}
+{"year":"2022","title":"Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping","authors":["J He, X Li, D Yu, H Zhang, J Kulkarni, YT Lee… - arXiv preprint arXiv …, 2022"],"snippet":"Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the two axes are possible and provide affirmative answers …","url":["https://arxiv.org/pdf/2212.01539"]}
+{"year":"2022","title":"Exploring Transformers models for Emotion Recognition: a comparision of BERT, DistilBERT, RoBERTa, XLNET and ELECTRA","authors":["D Cortiz - 2022 3rd International Conference on Control …, 2022"],"snippet":"This paper investigates the performance of different Transformers Models for Emotion Recognition, a specific NLU (Natural Language Understanding) task in Affective Computing. We implemented and finetuned different transformers …","url":["https://dl.acm.org/doi/abs/10.1145/3562007.3562051"]}
+{"year":"2022","title":"Exposing Cross-Lingual Lexical Knowledge from Multilingual Sentence Encoders","authors":["I Vulić, G Glavaš, F Liu, N Collier, EM Ponti… - arXiv preprint arXiv …, 2022"],"snippet":"Pretrained multilingual language models (LMs) can be successfully transformed into multilingual sentence encoders (SEs; eg, LaBSE, xMPNET) via additional fine-tuning or model distillation on parallel data. However, it remains uncertain how to best …","url":["https://arxiv.org/pdf/2205.00267"]}
+{"year":"2022","title":"Exposing the many biases in machine learning","authors":["S Richardson - Business Information Review, 2022"],"snippet":"In recent years, there have been numerous articles highlighting issues with bias in machine learning algorithms underpinning the use of AI in decision making. Specifically, algorithms trained on historical real-world observations. However, less …","url":["https://journals.sagepub.com/doi/abs/10.1177/02663821221121024"]}
+{"year":"2022","title":"Exposure and Emergence in Usage-Based Grammar: Computational Experiments in 35 Languages","authors":["J Dunn - arXiv preprint arXiv:2211.14160, 2022"],"snippet":"This paper uses computational experiments to explore the role of exposure in the emergence of construction grammars. While usage-based grammars are hypothesized to depend on a learner's exposure to actual language use, the …","url":["https://arxiv.org/pdf/2211.14160"]}
+{"year":"2022","title":"Extended Overview of HIPE-2022: Named Entity Recognition and Linking in Multilingual Historical Documents","authors":["M Ehrmann, M Romanello, S Najem-Meyer, A Doucet… - Working Notes of CLEF, 2022"],"snippet":"This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places and other Entities), a shared task on named entity recognition and linking in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 …","url":["http://ceur-ws.org/Vol-3180/paper-83.pdf"]}
+{"year":"2022","title":"Extracting Cultural Commonsense Knowledge at Scale","authors":["TP Nguyen, S Razniewski, A Varde, G Weikum - arXiv preprint arXiv:2210.07763, 2022"],"snippet":"Structured knowledge is important for many AI applications. Commonsense knowledge, which is crucial for robust human-centric AI, is covered by a small number of structured knowledge projects. However, they lack knowledge about …","url":["https://arxiv.org/pdf/2210.07763"]}
+{"year":"2022","title":"Extracting Impact Model Narratives from Social Services' Text","authors":["B Gajderowicz, D Rosu, MS Fox - 2022"],"snippet":"Named entity recognition (NER) is an important task in narration extraction. Narration, as a system of stories, provides insights into how events and characters in the stories develop over time. This paper proposes an architecture for NER on a corpus …","url":["http://ceur-ws.org/Vol-3117/paper6.pdf"]}
+{"year":"2022","title":"Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek","authors":["A Vaca, A Segurado, D Betancur, A Barbero - Proceedings of the 4th Financial …, 2022"],"snippet":"This paper describes the three summarization systems submitted to the Financial Narrative Summarization Shared Task (FNS-2022). We developed a task-specific extractive summarization method for the reports in English. It was based on a …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/FNP/pdf/2022.fnp-1.8.pdf"]}
+{"year":"2022","title":"Extractive Question Answering on Queries in Hindi and Tamil","authors":["A Thirumala, E Ferracane - arXiv preprint arXiv:2210.06356, 2022"],"snippet":"… This is achieved by training the model on a large corpus of webcrawl data called the Common Crawl. The Common Crawl is a dataset that contains over 7 years of webcrawl data in over 40 languages. The question answering head applied to XLM- …","url":["https://arxiv.org/pdf/2210.06356"]}
+{"year":"2022","title":"Extreme Multilabel Text Classification on Indonesian Tax Court Ruling using Single Channel CNN and IndoBERT Embedding","authors":["IN Khasanah, AA Krisnadhi - 2021 6th International Workshop on Big Data and …, 2021"],"snippet":"Manual searching for legal basis such as paragraphs, articles, and laws when preparing for a tax court hearing is time-consuming. In this paper, we use extreme multilabel text classification approach to predict paragraphs, articles, and laws …","url":["https://ieeexplore.ieee.org/abstract/document/9631855/"]}
+{"year":"2022","title":"Face-Dubbing++: Lip-Synchronous, Voice Preserving Translation of Videos","authors":["A Waibel, M Behr, FI Eyiokur, D Yaman, TN Nguyen… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper, we propose a neural end-to-end system for voice preserving, lip-synchronous translation of videos. The system is designed to combine multiple component models and produces a video of the original speaker speaking in the target …","url":["https://arxiv.org/pdf/2206.04523"]}
+{"year":"2022","title":"Fact-checking Multidimensional Statistic Claims in French","authors":["O Balalau, S Ebel, T Galizzi, A Deiana, E Gautreau… - TTO 2022-Truth and Trust …, 2022"],"snippet":"To strengthen public trust and counter disinformation, computational fact-checking, leveraging digital data sources, attracts interest from the journalists and the computer science community. A particular class of interesting data sources …","url":["https://hal.archives-ouvertes.fr/hal-03791175/document"]}
+{"year":"2022","title":"FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization","authors":["D Wan, M Bansal - arXiv preprint arXiv:2205.07830, 2022"],"snippet":"We present FactPEGASUS, an abstractive summarization model that addresses the problem of factuality during pre-training and fine-tuning: (1) We augment the sentence selection strategy of PEGASUS's (Zhang et al., 2020) pre-training objective …","url":["https://arxiv.org/pdf/2205.07830"]}
+{"year":"2022","title":"Factual Consistency of Multilingual Pretrained Language Models","authors":["C Fierro, A Søgaard - arXiv preprint arXiv:2203.11552, 2022"],"snippet":"Pretrained language models can be queried for factual knowledge, with potential applications in knowledge base acquisition and tasks that require inference. However, for that, we need to know how reliable this knowledge is, and recent work …","url":["https://arxiv.org/pdf/2203.11552"]}
+{"year":"2022","title":"Fair and Optimal Classification via Transports to Wasserstein-Barycenter","authors":["R Xian, L Yin, H Zhao - arXiv preprint arXiv:2211.01528, 2022"],"snippet":"… The task is to determine the occupation (out of 28) of female and male individuals by their biography in text; the biographies, occupations and genders are mined from the Common Crawl corpus. Gender is the sensitive attribute, and to which certain …","url":["https://arxiv.org/pdf/2211.01528"]}
+{"year":"2022","title":"Fake news detection: When complex problems demand complex solutions","authors":["C Oliva, IP Marín, LF Lago-Fernández… - 2021"],"snippet":"Fake news detection is one of the most challenging problems in today's information and communication systems. In this article we address the challenge of detecting the generation and spreading of misleading information in the specific scenario of …","url":["https://digital.csic.es/bitstream/10261/257188/1/main_applied_intelligence.pdf"]}
+{"year":"2022","title":"Fake or Genuine? Contextualised Text Representation for Fake Review Detection","authors":["R Mohawesh, S Xu, M Springer, M Al-Hawawreh… - arXiv preprint arXiv …, 2021"],"snippet":"… Along with the English Wikipedia and book corpora, RoBERTa is pre-trained on the Common Crawl News dataset, comprising 63 million English-language news stories. RoBERTa base architecture consists of 768 hidden layers, 12 layers, 125 …","url":["https://arxiv.org/pdf/2112.14343"]}
+{"year":"2022","title":"FastClass: A Time-Efficient Approach to Weakly-Supervised Text Classification","authors":["T Xia, Y Wang, Y Tian, Y Chang - arXiv preprint arXiv:2212.05506, 2022"],"snippet":"Weakly-supervised text classification aims to train a classifier using only class descriptions and unlabeled data. Recent research shows that keyword-driven methods can achieve state-of-the-art performance on various tasks. However, these …","url":["https://arxiv.org/pdf/2212.05506"]}
+{"year":"2022","title":"FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners","authors":["H Liu, X Geng, L Lee, I Mordatch, S Levine, S Narang… - arXiv preprint arXiv …, 2022"],"snippet":"Large language models (LLM) trained using the next-token-prediction objective, such as GPT3 and PaLM, have revolutionized natural language processing in recent years by showing impressive zero-shot and few-shot capabilities across a wide …","url":["https://arxiv.org/pdf/2210.13432"]}
+{"year":"2022","title":"FD-GATDR: A Federated-Decentralized-Learning Graph Attention Network for Doctor Recommendation Using EHR","authors":["L Bi, Y Wang, F Zhang, Z Liu, Y Cai, E Zhao - arXiv preprint arXiv:2207.05750, 2022"],"snippet":"… The GloVe model is loaded with the pretrained parameters on Common Crawl which has 840B tokens and 2.2M vocab [11]. Each word is converted to a 300-dimension vector. Then the model is fine-tuned with LSTM for the classification. …","url":["https://arxiv.org/pdf/2207.05750"]}
+{"year":"2022","title":"Feasibility study of long-form question answering","authors":["S Antikainen - 2022"],"snippet":"Long-form question answering (LFQA) is a challenging natural language processing task as it asks to produce paragraph-length answers to questions. Meaningful progress in LFQA would significantly speed up how fast people can seek information …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/112850/master_Antikainen_Simo_2022.pdf?sequence=1"]}
+{"year":"2022","title":"Feature-based Question Routing in Community Question Answering Platforms","authors":["S Sorkhani, R Etemadi, A Bigdeli, M Zihayat, E Bagheri - Information Sciences, 2022"],"snippet":"… To do so, we use the Fasttext model with the pre-trained embeddings on the Common Crawl dataset 4 to obtain embedding vectors for question’s tags and tags of the questions answered by the user. Subsequently, we compute this feature for …","url":["https://www.sciencedirect.com/science/article/pii/S0020025522006661"]}
+{"year":"2022","title":"Few shot learning with fine-tuned language model for suicidal text detection","authors":["S Varma, S Shivam, B Ray, A Banerjee - 2022"],"snippet":"… The corpus used for pre-training the language model has been obtained from Wikipedia and Common crawl web scrapes which are vast and prone to have fairly low quality. Therefore, cleaning methods like deduplication, removal of incomplete …","url":["https://www.researchsquare.com/article/rs-2392230/latest.pdf"]}
+{"year":"2022","title":"Few-shot learning with language models: Learning from instructions and contexts","authors":["T Schick - 2022"],"snippet":"Pretraining deep neural networks to perform language modeling–that is, to reconstruct missing words from incomplete pieces of text–has brought large improvements throughout natural language processing (NLP). However, even …","url":["https://edoc.ub.uni-muenchen.de/29867/1/Schick_Timo.pdf"]}
+{"year":"2022","title":"Few-shot Learning with Retrieval Augmented Language Models","authors":["G Izacard, P Lewis, M Lomeli, L Hosseini, F Petroni… - arXiv preprint arXiv …, 2022"],"snippet":"… Another explanation might be that Wikipedia is a higher-quality and denser source of knowledge than common crawl. Second, when using a common crawl index, we observe that pre-training on Wikipedia data leads to lower performance …","url":["https://arxiv.org/pdf/2208.03299"]}
+{"year":"2022","title":"Few-Shot Natural Language Processing by Meta-Learning Without Labeled Data","authors":["T Bansal - 2022"],"snippet":"Humans show a remarkable capability to accurately solve a wide range of problems efficiently--utilizing a limited amount of computation and experience. Deep learning models, by stark contrast, can be trained to be highly accurate on a narrow task …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=3507&context=dissertations_2"]}
+{"year":"2022","title":"Fight Against COVID-19 Misinformation via Clustering-Based Subset Selection Fusion Methods","authors":["Y Huang, Q Xu, S Wu, C Nugent, A Moore - 2022"],"snippet":"The worldwide COVID-19 pandemic has brought about a lot of changes in people’s life. It also emerges as a new challenge to information search services. This is because up to now our understanding about the virus is still limited, and there is a lot …","url":["http://ceur-ws.org/Vol-3138/paper2_jot.pdf"]}
+{"year":"2022","title":"Finding and Fixing Undesirable Behaviors in Pretrained Language Models","authors":["E Perez - 2022"],"snippet":"In machine learning, we often do not know how to specify the desired objective for our learning algorithms. For example, we typically train models to answer questions correctly by using a proxy objective: training models to answer questions as people …","url":["https://ethanperez.net/thesis.pdf"]}
+{"year":"2022","title":"Finding Memo: Extractive Memorization in Constrained Sequence Generation Tasks","authors":["V Raunak, A Menezes - arXiv preprint arXiv:2210.12929, 2022"],"snippet":"Memorization presents a challenge for several constrained Natural Language Generation (NLG) tasks such as Neural Machine Translation (NMT), wherein the proclivity of neural models to memorize noisy and atypical samples reacts adversely …","url":["https://arxiv.org/pdf/2210.12929"]}
+{"year":"2022","title":"Findings of the 2022 Conference on Machine Translation (WMT22)","authors":["T Kocmi, R Bawden, O Bojar, A Dvorkovich…"],"snippet":"This paper presents the results of the General Machine Translation Task organised as part of the Conference on Machine Translation (WMT) 2022. In the general MT task, participants were asked to build machine translation systems for any of 11 …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.1.pdf"]}
+{"year":"2022","title":"Findings of the WMT 2022 Biomedical Translation Shared Task: Monolingual Clinical Case Reports","authors":["M Neves, AJYA Siu, R Roller, P Thomas, MV Navarro…"],"snippet":"In the seventh edition of the WMT Biomedical Task, we addressed a total of seven language pairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian. This year’s test sets covered …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.69.pdf"]}
+{"year":"2022","title":"Findings of the WMT 2022 shared task on large-scale machine translation evaluation for african languages","authors":["DI Adelani, MMI Alam, A Anastasopoulos, A Bhagia… - Proceedings of the Seventh …, 2022"],"snippet":"… We then performed bitext mining against 21.5 billion English sentences from Common Crawl, and 3.3 million sentences in French, respectively. These resources as well as the sentence encoders were made available to the participants of this …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.72.pdf"]}
+{"year":"2022","title":"Fine-grained Czech News Article Dataset: An Interdisciplinary Approach to Trustworthiness Analysis","authors":["M Boháček, M Bravanský, F Trhlík, V Moravec - arXiv preprint arXiv:2212.08550, 2022"],"snippet":"We present the Verifee Dataset: a novel dataset of news articles with fine-grained trustworthiness annotations. We develop a detailed methodology that assesses the texts based on their parameters encompassing editorial transparency, journalist …","url":["https://arxiv.org/pdf/2212.08550"]}
+{"year":"2022","title":"Fine-grained semantic type discovery for heterogeneous sources using clustering","authors":["F Piai, P Atzeni, P Merialdo, D Srivastava - The VLDB Journal, 2022"],"snippet":"We focus on the key task of semantic type discovery over a set of heterogeneous sources, an important data preparation task. We consider the challenging setting of multiple Web data sources in a vertical domain, which present sparsity of data and a …","url":["https://link.springer.com/article/10.1007/s00778-022-00743-3"]}
+{"year":"2022","title":"Fine-tuning and multilingual pre-training for abstractive summarization task for the Arabic language","authors":["M Kahla, A Novák, ZG Yang - Annales Mathematicae et Informaticae"],"snippet":"… We chose to download Arabic Deutsche Welle resources from Common Crawl4, as this solution does not interfere with the site. A very positive aspect of this resource is that the items downloaded from the DW news website address a wide range of …","url":["http://publikacio.uni-eszterhazy.hu/7512/1/AMI_online_1323.pdf"]}
+{"year":"2022","title":"Fine-tuning Pre-trained Language Models with Noise Stability Regularization","authors":["H Hua, X Li, D Dou, CZ Xu, J Luo - arXiv preprint arXiv:2206.05658, 2022"],"snippet":"The advent of large-scale pre-trained language models has contributed greatly to the recent progress in natural language processing. Many state-of-the-art language models are first trained on a large text corpus and then fine-tuned on downstream …","url":["https://arxiv.org/pdf/2206.05658"]}
+{"year":"2022","title":"FINE-TUNING TRANSFORMERS: ASSESSMENTS OF","authors":["Z Sun - 2022"],"snippet":"… in the development of pre-trained systems such as BERT [4](Bidirectional Encoder Representations from Transformers) and GPT [23](Generative Pre-trained Transformer), which was trained on large language datasets such as the Wikipedia …","url":["https://scholarworks.csun.edu/bitstream/handle/10211.3/223189/Sun-Zhen-thesis-2022.pdf?sequence=1"]}
+{"year":"2022","title":"FitLayout: An RDF-Based Framework and Toolkit for Web Page Content Analysis","authors":["R Burget, H Salem"],"snippet":"Despite the ongoing development of technologies that allow the publication of structured information within web pages, there still exist many web sources that publish useful data solely in the form of plain HTML documents. The data published …","url":["https://www.semantic-web-journal.net/system/files/swj3217.pdf"]}
+{"year":"2022","title":"FLightNER: A Federated Learning Approach to Lightweight Named-Entity Recognition","authors":["MPA Abadeer - 2022"],"snippet":"We introduce FLightNER, a Federated Learning model that extends a state-of-the-art Named-Entity Recognition model using prompt-tuning known as LightNER. FLightNER allows the aggregation of only the trainable parameters of LightNER …","url":["https://curve.carleton.ca/system/files/etd/3b9a9b49-620f-45df-a224-9ec2a6744015/etd_pdf/c91661bd3335b24f70ac9658f97e40e0/abadeer-flightnerafederatedlearningapproachtolightweight.pdf"]}
+{"year":"2022","title":"Forecasting Future World Events with Neural Networks","authors":["A Zou, T Xiao, R Jia, J Kwon, M Mazeika, R Li, D Song… - arXiv preprint arXiv …, 2022"],"snippet":"… To this end, we provide a corpus of news articles scraped from CommonCrawl news (Nagel, 2016; Hamborg et al., 2017) that is organized by publish date. The articles were generated between 2016 to mid-2022 and total more than 200GB of …","url":["https://arxiv.org/pdf/2206.15474"]}
+{"year":"2022","title":"Formal Mathematics Statement Curriculum Learning","authors":["S Polu, JM Han, K Zheng, M Baksys, I Babuschkin…"],"snippet":"We explore the use of expert iteration in the context of language modeling applied to formal mathematics. We show that at same compute budget, expert iteration, by which we mean proof search interleaved with learning, dramatically outperforms …","url":["https://cdn.openai.com/papers/Formal_Mathematics_Statement_Curriculum_Learning__ICML_2022.pdf"]}
+{"year":"2022","title":"Formulating Automated Responses to Cognitive Distortions for CBT Interactions","authors":["I de Toledo Rodriguez, G Salton, R Ross - … of The Fourth International Conference on …, 2021"],"snippet":"… 2020), trained on a cleaned version of the Common Crawl corpus (C4). The published model checkpoints have been pre-trained in a diverse variety of unsupervised and supervised tasks (language modelling, word embedding, machine translation …","url":["https://aclanthology.org/2021.icnlsp-1.13.pdf"]}
+{"year":"2022","title":"FP8 Formats for Deep Learning","authors":["P Micikevicius, D Stosic, N Burgess, M Cornea… - arXiv preprint arXiv …, 2022"],"snippet":"FP8 is a natural progression for accelerating deep learning training inference beyond the 16-bit formats common in modern processors. In this paper we propose an 8-bit floating point (FP8) binary interchange format consisting of two encodings …","url":["https://arxiv.org/pdf/2209.05433"]}
+{"year":"2022","title":"FPSRS: A Fusion Approach for Paper Submission Recommendation System","authors":["ST Huynh, N Dang, DH Nguyen, PT Huynh, BT Nguyen - arXiv preprint arXiv …, 2022"],"snippet":"… We remove single letters that likely do not have pretrained weights in wellknown pretrained word vectors like FastText Common Crawl4. 4. We remove words within stopwords downloaded from the Natural Language Toolkit (NLTK5) and additional …","url":["https://arxiv.org/pdf/2205.05965"]}
+{"year":"2022","title":"French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English","authors":["A Névéol, Y Dupont, J Bezançon, K Fort - ACL 2022-60th Annual Meeting of the …, 2022"],"snippet":"Warning: This paper contains explicit statements of offensive stereotypes which may be upsetting. Much work on biases in natural language processing has addressed biases linked to the social and cultural experience of English speaking individuals in …","url":["https://hal.inria.fr/hal-03629677/document"]}
+{"year":"2022","title":"From Bag-of-Words to Transformers: A Deep Dive into the Participation in the eRisk Early Risk Detection of Depression Tasks with Classical and New Approaches","authors":["H Damm, M Trotzek, S Koitka, H Schäfer… - … : The First Five Years of the …, 2022"],"snippet":"… 12 For this work, a 50-dimensional GloVe model trained on Wikipedia and the Gigaword 5 news corpus as well as a 300-dimensional GloVe model trained on Common Crawl were chosen. In addition, three 300-dimensional pre-trained …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=03KJEAAAQBAJ&oi=fnd&pg=PA61&dq=commoncrawl&ots=ilEvY4CTlF&sig=dsM8zq8Ay1-T1sLV96NBraKKox4"]}
+{"year":"2022","title":"From Bag-of-Words to Transformers: A Deep Dive into the Participation in the eRisk Tasks with Classical and New Approaches","authors":["H Damm, M Trotzek, S Koitka, H Schäfer… - Early Detection of Mental …, 2022"],"snippet":"… Footnote 12 For this work, a 50-dimensional GloVe model trained on Wikipedia and the Gigaword 5 news corpus as well as a 300-dimensional GloVe model trained on Common Crawl were chosen. In addition, three 300-dimensional pre-trained …","url":["https://link.springer.com/chapter/10.1007/978-3-031-04431-1_4"]}
+{"year":"2022","title":"From tabular data to knowledge graphs: A survey of semantic table interpretation tasks and methods","authors":["J Liu, Y Chabot, R Troncy, VP Huynh, T Labbé… - Journal of Web Semantics, 2022"],"snippet":"Tabular data often refers to data that is organized in a table with rows and columns. We observe that this data format is widely used on the Web and within enterprise data repositories. Tables potentially contain rich semantic information that still needs …","url":["https://www.sciencedirect.com/science/article/pii/S1570826822000452"]}
+{"year":"2022","title":"Fully Automated Detection of Formal Thought Disorder with Time-series Augmented Representations for Detection of Incoherent Speech (TARDIS)","authors":["W Xu, W Wang, J Portanova, A Chander, A Campbell… - Journal of Biomedical …, 2022"],"snippet":"… For the current research, we used publicly available pre-trained vectors derived using the FastText [39] package 8 consisting of 2-million-word vectors trained on a corpus derived from Common Crawl 9 . Individual words are represented by their …","url":["https://www.sciencedirect.com/science/article/pii/S1532046422000144"]}
+{"year":"2022","title":"Fusion of Remote Sensing Images and Social Media Text Messages for Building Function Classification","authors":["M Häberle - 2022"],"snippet":"Detailed data about urban land-use, like building functions, is useful to governments for resource planning. To detect building functions, satellite imagery could be too course. In this work, individual buildings from 42 cities are classified with multilingual …","url":["https://mediatum.ub.tum.de/doc/1637448/document.pdf"]}
+{"year":"2022","title":"FuzzyDedup: Secure Fuzzy Deduplication for Cloud Storage","authors":["T Jiang, X Yuan, Y Chen, K Cheng, L Wang, X Chen… - IEEE Transactions on …, 2022"],"snippet":"Data deduplication is of critical importance to reduce the storage cost for clients and to relieve the unnecessary storage pressure for cloud servers. While various techniques have been proposed for secure deduplication of identical files/blocks …","url":["https://ieeexplore.ieee.org/abstract/document/9804218/"]}
+{"year":"2022","title":"Galactica: A Large Language Model for Science","authors":["R Taylor, M Kardas, G Cucurull, T Scialom, A Hartshorn… - arXiv preprint arXiv …, 2022"],"snippet":"… While we do pick up some high-school level content through encyclopedias, textbooks and the filtered CommonCrawl, this amounts to a small quantity of tokens (a few billion). We leave the question of how to capture more of this base scientific …","url":["https://arxiv.org/pdf/2211.09085"]}
+{"year":"2022","title":"Gauge against the machine: improving representations within sociotechnical instruments to enrich context and identify biases","authors":["J Minot - 2022"],"snippet":"The proliferation of digital data across all areas of society has transformed our ability to hypothesize, study, and understand social systems. From this richness of data we have seen the development of innovative instruments to study---and make decisions …","url":["https://scholarworks.uvm.edu/cgi/viewcontent.cgi?article=2607&context=graddis"]}
+{"year":"2022","title":"Gauging Engagement: Measuring Student Response to a Large-Scale College Advising Field Experiment","authors":["BH Kim, K Meyer, A Choe"],"snippet":"Interactive, text message-based advising programs have become an increasingly common strategy to support college access and success for underrepresented student populations. Despite the proliferation of these programs, we know relatively …","url":["https://edworkingpapers.org/sites/default/files/ai22-567.pdf"]}
+{"year":"2022","title":"Gender and Racial Stereotype Detection in Legal Opinion Word Embeddings","authors":["S Matthews, J Hudzina, D Sepehr - 2022"],"snippet":"… In addition, the instrument/weapons control display equivalent effect sizes between Caliskan’s Common Crawl corpus experiments and the legal … Gender Effects: While the effect sizes were comparable between the Common Crawl corpus …","url":["https://www.aaai.org/AAAI22Papers/AISI-10870.MatthewsS.pdf"]}
+{"year":"2022","title":"Gender Bias in Machine Translation Systems","authors":["S Ullmann - Artificial Intelligence and Its Discontents, 2022"],"snippet":"… The data was originally obtained from Common Crawl, a free online repository consisting of large amounts of internet data. Consequently, the data represents a variety of registers from formal to informal, slang and even archaic vocabulary due to …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88615-8_7"]}
+{"year":"2022","title":"Gender Bias in Meta-Embeddings","authors":["M Kaneko, D Bollegala, N Okazaki - arXiv preprint arXiv:2205.09867, 2022"],"snippet":"Combining multiple source embeddings to create meta-embeddings is considered effective to obtain more accurate embeddings. Different methods have been proposed to develop meta-embeddings from a given set of source embeddings …","url":["https://arxiv.org/pdf/2205.09867"]}
+{"year":"2022","title":"Generating Extended and Multilingual Summaries with Pre-trained Transformers","authors":["R Calizzano, M Ostendorff, Q Ruan, G Rehm"],"snippet":"Almost all summarisation methods and datasets focus on a single language and short summaries. We introduce a new dataset called WikinewsSum for English, German, French, Spanish, Portuguese, Polish, and Italian summarisation tailored for …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.175.pdf"]}
+{"year":"2022","title":"Generating Full Length Wikipedia Biographies: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies","authors":["A Fan, C Gardent - arXiv preprint arXiv:2204.05879, 2022"],"snippet":"… Given a person’s name, one or more occupation(s), and CommonCrawl as a source of … name, one or more occupations, a section header, and CommonCrawl as a retrieval corpus. … We reject all CommonCrawl links from Wikipedia, to prevent …","url":["https://arxiv.org/pdf/2204.05879"]}
+{"year":"2022","title":"Generating Music using AI","authors":["E Rickard"],"snippet":"Network speakers are used in public spaces for public announcements and sometimes to play background music. To play music, a special commercial music licence is required, specifically made for use in public environments. However …","url":["https://lup.lub.lu.se/student-papers/record/9093922/file/9093927.pdf"]}
+{"year":"2022","title":"Generating Role-Playing Game Quest Descriptions With the GPT-2 Language Model","authors":["S Värtinen - 2022"],"snippet":"Recent advances in artificial intelligence research have brought forth text-generating language models with promising computational storytelling capabilities. This thesis leveraged one of the most successful Transformer models, GPT-2, to automatically …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/112852/master_V%C3%A4rtinen_Susanna_2022.pdf?sequence=1"]}
+{"year":"2022","title":"Generating Scientific Definitions with Controllable Complexity","authors":["T August, K Reinecke, NA Smith"],"snippet":"… We use scientific abstracts, rather than general audience text like Wikipedia or the Common Crawl, for two reasons. First, scientific terms are originally introduced and most commonly used in research papers, making them the most reliable source for …","url":["https://homes.cs.washington.edu/~reinecke/Publications_files/August_ACL2022.pdf"]}
+{"year":"2022","title":"Generating Word Embeddings for the Azerbaijani Language and Their Empirical Evaluation on Intrinsic and Extrinsic Evaluation Tasks","authors":["U Suleymanov - 2021"],"snippet":"… al. has also partitioned their data corpora into smaller datasets, such as Common Crawl, Wikipedia, WebText and etc. The machine learning architecture they have built, is one of the largest language models ever built with 175 billion parameters …","url":["http://dspace.khazar.org/bitstream/20.500.12323/5448/1/Generating%20Word%20Embeddings%20for%20the%20Azerbaijani%20Language%20and%20Their%20Empirical%20Evaluation%20on%20Intrinsic%20and%20Extrinsic%20Evaluation%20Tasks.pdf"]}
+{"year":"2022","title":"Getting along to get ahead: Predictors of success in an online competitive social environment","authors":["SR Curtis - 2022"],"snippet":"The University of Nevada, Reno Getting along to get ahead: Predictors of success in an online competitive social environment A d Page 1 The University of Nevada, Reno Getting along to get ahead: Predictors of success in an online competitive …","url":["https://scholarworks.unr.edu/bitstream/handle/11714/8172/Curtis_unr_0139D_13732.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Getting to the root of linguistic alignment: Testing the predictions of Interactive Alignment across developmental and biological variation in language skill","authors":["R Foushee, D Byrne, M Casillas, S Goldin-Meadow - 2022"],"snippet":"Linguistic alignment—the contingent reuse of our interlocutors' language at all levels of linguistic structure—pervades human dialogue. Here, we design unique measures to capture the degree of linguistic alignment between interlocutors' …","url":["https://osf.io/tqrew/download"]}
+{"year":"2022","title":"Global Readiness of Language Technology for Healthcare: What would it Take to Combat the Next Pandemic?","authors":["I Mondal, K Ahuja, M Jain, JO Neil, K Bali… - arXiv preprint arXiv …, 2022"],"snippet":"The COVID-19 pandemic has brought out both the best and worst of language technology (LT). On one hand, conversational agents for information dissemination and basic diagnosis have seen widespread use, and arguably, had an important …","url":["https://arxiv.org/pdf/2204.02790"]}
+{"year":"2022","title":"Global-locality preserving projection for word embedding","authors":["B Wang, Y Sun, Y Chu, Z Yang, H Lin - … Journal of Machine Learning and Cybernetics, 2022"],"snippet":"… -the Common Crawl corpus consisting of 840b tokens and a vocabulary containing 2.2 M words with 300-dimensional, the Common Crawl (… Here we use the pre-trained word embedding of the Common Crawl corpus (840b tokens, 2.2 M …","url":["https://link.springer.com/article/10.1007/s13042-022-01574-y"]}
+{"year":"2022","title":"GPT-3 and Friends: Transformers in Natural Language Processing","authors":["L Reber - FMS-BERICHTE, 2022"],"snippet":"In 2020, the British newspaper “The Guardian” published an editorial written in its entirety by an artificial intelligence called “Generative Pre-trained Transformer 3”. GPT-3 is one of several “Natural Language Processors”(NLPs), allowing a computer …","url":["https://www.researchgate.net/profile/Andrea-Reindl/publication/364180536_FMS-BERICHTE_SOMMERSEMESTER_2022/links/633d93879cb4fe44f305a2dc/FMS-BERICHTE-SOMMERSEMESTER-2022.pdf#page=63"]}
+{"year":"2022","title":"GPT-3 and InstructGPT: technological dystopianism, utopianism, and “Contextual” perspectives in AI ethics and industry","authors":["A Chan - AI and Ethics, 2022"],"snippet":"This paper examines the ethical solutions raised in response to OpenAI’s language model Generative Pre-trained Transformer-3 (GPT-3) a year and a half from its release. I argue that hype and fear about GPT-3, even within the Natural Language …","url":["https://link.springer.com/article/10.1007/s43681-022-00148-6"]}
+{"year":"2022","title":"GPT-3 for Few-Shot Dialogue State Tracking","authors":["N Pezzotti"],"snippet":"GPT-3 (Brown et al., 2020) has attracted considerable attention due to its superior performance across a wide range of Natural Language Processing (NLP) tasks, especially with its powerful and versatile in-context few-shot learning ability. That is …","url":["https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/gpt_3_for_few_shot_dialogue_state_tracking.pdf"]}
+{"year":"2022","title":"GPT-NeoX-20B: An Open-Source Autoregressive Language Model","authors":["S Black, S Biderman, E Hallahan, Q Anthony, L Gao…"],"snippet":"GPT-NeoX-20B is a 20 billion parameter autoregressive language model whose weights will be made freely and openly available to the public through a permissive license. It is, to the best of our knowledge, the largest dense autoregressive model …","url":["http://eaidata.bmk.sh/data/GPT_NeoX_20B.pdf"]}
+{"year":"2022","title":"GPTs at Factify 2022: Prompt Aided Fact-Verification","authors":["PK Sahu, S Aggarwal, T Gupta, G Das - arXiv preprint arXiv:2206.14913, 2022","S Aggarwal, P Sahu, T Gupta, G Das - Proceedings of De-Factify: Workshop on …, 2022"],"snippet":"One of the most pressing societal issues is the fight against false news. The false claims, as difficult as they are to expose, create a lot of damage. To tackle the problem, fact verification becomes crucial and thus has been a topic of interest …","url":["http://ceur-ws.org/Vol-3199/paper11.pdf","https://arxiv.org/pdf/2206.14913"]}
+{"year":"2022","title":"Grammatical Error Correction: A Survey of the State of the Art","authors":["C Bryant, Z Yuan, MR Qorib, H Cao, HT Ng, T Briscoe - arXiv preprint arXiv …, 2022"],"snippet":"Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text. The task not only includes the correction of grammatical errors, such as missing prepositions and mismatched subject-verb agreement, but …","url":["https://arxiv.org/pdf/2211.05166"]}
+{"year":"2022","title":"Granular Emotion Detection for Multi-Class Sentiment Analysis in Social Media","authors":["RH Frye - 2022"],"snippet":"… XLNet was trained on many of the same or similar datasets as BERT and RoBERTa, including CommonCrawl, BooksCorpus, and English … A clean derivation of the CommonCrawl Corpus was used in pretraining XLM-R, with one …","url":["https://search.proquest.com/openview/19befd3b5703b8663bf55b49a0bbf582/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"GraphIC: A graph-based approach for identifying complaints from code-mixed product reviews","authors":["A Singh, S Saha - Expert Systems with Applications, 2022"],"snippet":"… Wikipedia’s and Common Crawl’s publicly available corpora for 17 Indian languages were employed for monolingual data. PMINDIA and Dakshina corpora were used to obtain translated and transliterated data for parallel segments. For code-mixed …","url":["https://www.sciencedirect.com/science/article/pii/S0957417422024630"]}
+{"year":"2022","title":"GREENER: Graph Neural Networks for News Media Profiling","authors":["P Panayotov, U Shukla, HT Sencar, M Nabeel, P Nakov - arXiv preprint arXiv …, 2022"],"snippet":"We study the problem of profiling news media on the Web with respect to their factuality of reporting and bias. This is an important but under-studied problem related to disinformation and \"fake news\" detection, but it addresses the issue at a …","url":["https://arxiv.org/pdf/2211.05533"]}
+{"year":"2022","title":"GRILLBot: A flexible conversational agent for solving complex real-world tasks","authors":["C Gemmell, S Fischer, I Mackie, P Owoicho, F Rossetto…"],"snippet":"… We use Common Crawl to download the raw HTML for target domains and develop website-specific wrappers to extract semi-structured information about each task, ie title, author, description, ingredients, images, steps, ratings, videos, etc. We …","url":["https://assets.amazon.science/0c/2c/f214256a43bba8d97ade42c56be0/grillbot-a-flexible-conversational-agent-for-solving-complex-real-world-tasks.pdf"]}
+{"year":"2022","title":"GRILLBot: A multi-modal conversational agent for complex real-world tasks","authors":["C Gemmell, F Rossetto, I Mackie, P Owoicho, S Fischer… - Proceedings of the 23rd …, 2022"],"snippet":"… We use Common Crawl to download the raw HTML for target domains and develop website-specific wrappers to extract semi-structured information about each task, ie title, author, description, ingredients, images, steps, ratings, videos, infoboxes, FAQs. …","url":["https://aclanthology.org/2022.sigdial-1.63.pdf"]}
+{"year":"2022","title":"GRILLBot: An Assistant for Real-World Tasks with Neural Semantic Parsing and Graph-Based Representations","authors":["C Gemmell, I Mackie, P Owoicho, F Rossetto, S Fischer… - arXiv preprint arXiv …, 2022"],"snippet":"… We use Common Crawl to download the raw HTML for target domains and develop website-specific wrappers to extract semi-structured information about each task, ie title, author, description, ingredients, images, steps, ratings, videos, infoboxes, FAQs. …","url":["https://arxiv.org/pdf/2208.14884"]}
+{"year":"2022","title":"Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generation","authors":["F Brahman, B Peng, M Galley, S Rao, B Dolan… - arXiv preprint arXiv …, 2022"],"snippet":"… The documents are citations in the Wikipedia article obtained by CommonCrawl or web pages returned by Google Search. Each instance in our data has 40 grounding passages. Note that our dataset is distantly supervised, and these …","url":["https://arxiv.org/pdf/2212.01956"]}
+{"year":"2022","title":"Grounding Language by Seeing, Hearing, and Interacting","authors":["R Zellers - 2022"],"snippet":"As humans, our understanding of language is grounded in a rich mental model about \"how the world works.\" As children, we learn this mental model gradually. We take in raw perceptual input about the world through all of our senses, and learn to …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48898/Zellers_washington_0250E_24408.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Grounding Language Models on External Sources: A Comparison of Knowledge Graphs and Unstructured Text","authors":["T Kaminski"],"snippet":"… To get an idea of the size, WebText, for example, consists of 40GB of text from 8 million documents scraped from the internet, but an even larger example is the corpus used to train T5 [81], named C4, which consists of 750GB of text derived from …","url":["https://isl.anthropomatik.kit.edu/downloads/BA-Tom-Kaminski-final.pdf"]}
+{"year":"2022","title":"GROWN+ UP: A Graph Representation Of a Webpage Network Utilizing Pre-training","authors":["B Yeoh, H Wang - arXiv preprint arXiv:2208.02252, 2022"],"snippet":"… We can also pre-train on a more massive set of webpages from an identical time period as the target domain, as opposed to the relatively small CommonCrawl 2008 corpus that we used for all benchmarks in this work. Lastly, integrating image, audio …","url":["https://arxiv.org/pdf/2208.02252"]}
+{"year":"2022","title":"HalBERT at PoliticEs 2022: Are Machine Learning Algorithms better for Author Profiling?","authors":["CG Holgado, A Sinha - Development, 2022"],"snippet":"This paper presents an investigation of different machine and deep learning models for Author Profiling for the Shared Task PoliticEs: Spanish Author Profiling for Political Ideology at IberLEF 2022. We provide a broad comparative study to see …","url":["http://ceur-ws.org/Vol-3202/politices-paper5.pdf"]}
+{"year":"2022","title":"Handling and Presenting Harmful Text","authors":["L Derczynski, HR Kirk, A Birhane, B Vidgen - arXiv preprint arXiv:2204.14256, 2022"],"snippet":"… enormous internet-scraped datasets such as Common Crawl Corpus or WebText. As these unstructured corpora become larger, the risk of them containing harmful content increases, and the larger the dataset, the more difficult it is for humans to …","url":["https://arxiv.org/pdf/2204.14256"]}
+{"year":"2022","title":"Hate Speech and Offensive Language Detection in Bengali","authors":["M Das, S Banerjee, P Saha, A Mukherjee - arXiv preprint arXiv:2210.03479, 2022"],"snippet":"… 2020) is another form of Transformer model, pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. XLM-R was trained using a lot more data compared to m-BERT. Similar to BERT, it is a stack of transformer encoder …","url":["https://arxiv.org/pdf/2210.03479"]}
+{"year":"2022","title":"Hate speech and offensive language detection in Dravidian languages using deep ensemble framework","authors":["PK Roy, S Bhawal, CN Subalalitha - Computer Speech & Language, 2022"],"snippet":"… It is pretrained with 2.5 TB of CommonCrawl data in 100 languages. Due to the absence of language embedding it can result in much better performances in the case of code-switching and are much better compared to multilingual BERT …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000250"]}
+{"year":"2022","title":"HC4: A New Suite of Test Collections for Ad Hoc CLIR","authors":["D Lawrie, J Mayfield, D Oard, E Yang - arXiv preprint arXiv:2201.09992, 2022","DW Oard, E Yang"],"snippet":"… First, to develop a multilingual document collection that was easy to distribute, we chose the Common Crawl News Collection as the basis for the suite of collections. We applied automatic language identification to determine the language of each …","url":["https://arxiv.org/pdf/2201.09992","https://terpconnect.umd.edu/~oard/pdf/ecir22lawrie.pdf"]}
+{"year":"2022","title":"Health Talk: Understanding Practices of Popular Professional YouTubers","authors":["TT Phan, C Michoud, L Volpato, M del Rio Carral… - 2022"],"snippet":"Practices related to health are circulated widely on YouTube. With a health psychology perspective, we present a study to understand health and wellbeing-related practices of a group of popular, professional YouTubers from the audio-visual …","url":["http://publications.idiap.ch/attachments/papers/2022/Phan_MUM_2022.pdf"]}
+{"year":"2022","title":"HeLI-OTS, Off-the-shelf Language Identifier for Text","authors":["T Jauhiainen, H Jauhiainen, K Lindén"],"snippet":"This paper introduces HeLI-OTS, an off-the-shelf text language identification tool using the HeLI language identification method. The HeLI-OTS language identifier is equipped with language models for 200 languages and licensed for academic as …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.416.pdf"]}
+{"year":"2022","title":"HICEM: A High-Coverage Emotion Model for Artificial Emotional Intelligence","authors":["B Wortman, JZ Wang - arXiv preprint arXiv:2206.07593, 2022"],"snippet":"… Trained on Common Crawl and Wikipedia, this model provides a 300-dimensional embedding for each word. FastText was chosen over … We then once again proceeded with Facebook’s FastText models which have been trained on Common …","url":["https://arxiv.org/pdf/2206.07593"]}
+{"year":"2022","title":"Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth","authors":["L Dhulipala, D Eisenstat, J Łącki, V Mirronki, J Shi - arXiv preprint arXiv:2206.11654, 2022"],"snippet":"Obtaining scalable algorithms for hierarchical agglomerative clustering (HAC) is of significant interest due to the massive size of real-world datasets. At the same time, efficiently parallelizing HAC is difficult due to the seemingly sequential nature of the …","url":["https://arxiv.org/pdf/2206.11654"]}
+{"year":"2022","title":"Hierarchical Graph Decomposition for Natural Language Generation","authors":["L Jin - 2022"],"snippet":"Central to natural language understanding and generation is the ability to accurately model the semantics of text. We can frame understanding as parsing a semantic form from a given sentence that represents all sentences of equivalent meaning …","url":["https://search.proquest.com/openview/8bba4ec7c1c89c32f0af8202a5fd0c9b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding","authors":["L Liu, O Perez-Concha, A Nguyen, V Bennett, L Jorm - arXiv preprint arXiv …, 2022"],"snippet":"International Classification of Diseases (ICD) coding plays an important role in systematically classifying morbidity and mortality data. In this study, we propose a hierarchical label-wise attention Transformer model (HiLAT) for the explainable …","url":["https://arxiv.org/pdf/2204.10716"]}
+{"year":"2022","title":"Hierarchical template transformer for fine-grained sentiment controllable generation","authors":["L Yuan, J Wang, LC Yu, X Zhang - Information Processing & Management, 2022"],"snippet":"Existing methods for text generation usually fed the overall sentiment polarity of a product as an input into the seq2seq model to generate a relatively fluent review. However, these methods cannot express more fine-grained sentiment polarity …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322001546"]}
+{"year":"2022","title":"High-frequency words have higher frequencies in Turkish social sciences article","authors":["N Gürsakal, S Çelik, S Özdemir - Quality & Quantity, 2022"],"snippet":"Abstract Words, sentences, and paragraphs are the basis of texts. When we consider texts as data and want to establish a relationship between qualitative and quantitative perspectives, we can do this with the word frequencies in a text. We aim …","url":["https://link.springer.com/article/10.1007/s11135-022-01444-3"]}
+{"year":"2022","title":"High-Resource Methodological Bias in Low-Resource Investigations","authors":["M ter Hoeve, D Grangier, N Schluter - arXiv preprint arXiv:2211.07534, 2022"],"snippet":"The central bottleneck for low-resource NLP is typically regarded to be the quantity of accessible data, overlooking the contribution of data quality. This is particularly seen in the development and evaluation of low-resource systems via down sampling …","url":["https://arxiv.org/pdf/2211.07534"]}
+{"year":"2022","title":"Hints of Independence in a Pre-scripted World: On Controlled Usage of Open-domain Language Models for Chatbots in Highly Sensitive Domains","authors":["E Basar, I Hendrickx, E Krahmer, GJ de Bruijn, T Bosse - Proceedings of the 14th …, 2022"],"snippet":"… Because the training approach is unsupervised, it is possible to include a massive amount of data from various online sources, such as Wikipedia and CommonCrawl, with minimal human labour required. Hence, these neural language …","url":["https://www.scitepress.org/Papers/2022/109143/109143.pdf"]}
+{"year":"2022","title":"Hints of Independence Independence Independence in a Pre-scripted e-scripted e-scripted World: On Controlled Usage of Open-domain Open-domain Open-domain …","authors":["EBE Basar, I Hendrickx, E Krahmer, GJ de Bruijn… - 2022"],"snippet":"… Because the Because the Because the training approach is unsupervised, unsupervised, unsupervised, it is possible to include a massive amount of data from various online sources, such as Wikipedia and CommonCrawl, CommonCrawl …","url":["https://repository.uantwerpen.be/docstore/d:irua:11354"]}
+{"year":"2022","title":"Hipsters and the cool: A game theoretic analysis of identity expression, trends, and fads.","authors":["R Golman, EH Bugbee, A Jain, S Saraf - Psychological Review, 2021"],"snippet":"Cultural trends and popularity cycles can be observed all around us, yet our theories of social influence and identity expression do not explain what perpetuates these complex, often unpredictable social dynamics. We propose a theory of social identity …","url":["https://psycnet.apa.org/record/2022-16685-001"]}
+{"year":"2022","title":"Homepage2Vec: Language-Agnostic Website Embedding and Classification","authors":["S Lugeon, T Piccardi, R West - Proceedings of the International AAAI Conference on …, 2022"],"snippet":"… Following this intuition, we collected from Common Crawl,5 a large-scale sample of the Web, the 19 most frequent TLDs: .com, .org, .net, .info, … We consider the 30 most frequent metatags from a sample of the Common Crawl and represent their …","url":["https://ojs.aaai.org/index.php/ICWSM/article/download/19380/19152"]}
+{"year":"2022","title":"Homophobic and Hate Speech Detection Using Multilingual-BERT Model on Turkish Social Media","authors":["H Karayiğit, A Akdagli, Çİ ACI - Information Technology and Control, 2022"],"snippet":"… The GloVe algorithm used in this study is trained on Common Crawl [24]. There are 253K words in the vocabulary and the dimension size is 300. Training data is web-crawled multilingual text with 2,736B … Available: https:// commoncrawl.org/2021 …","url":["http://apbs.mersin.edu.tr/files/caci/Publications_003.pdf"]}
+{"year":"2022","title":"HOTTEST: Hate and offensive content identification in Tamil using transformers and enhanced STemming","authors":["R Rajalakshmi, S Selvaraj, P Vasudevan - Computer Speech & Language, 2022"],"snippet":"… It is a transformer-based model which is pre-trained on about 2500 Gigabytes of filtered CommonCrawl data. This data consists of texts from about 100 languages. The model is trained in a self-supervised manner which makes the model more …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000870"]}
+{"year":"2022","title":"How can we detect Homophobia and Transphobia? Experiments in a multilingual code-mixed setting for social media governance","authors":["BR Chakravarthi, A Hande, R Ponnusamy… - International Journal of …, 2022"],"snippet":"… XLM-R is pretrained over two terabytes of CommonCrawl data spanning over 100 languages to boost the performances in cross-lingual tasks. All these models use transformers as the building blocks of their architecture. The vital attribute is self-attention …","url":["https://www.sciencedirect.com/science/article/pii/S2667096822000623"]}
+{"year":"2022","title":"How Different is Stereotypical Bias in Different Languages?","authors":["IT Öztürk - 2022"],"snippet":"Recent studies have demonstrated how to assess the stereotypical bias in pre-trained mono-lingual language models for the English language. In this master thesis, we extend this approach to multi-lingual models and multiple languages to show the …","url":["https://epub.ub.uni-muenchen.de/93576/1/Oeztuerk_Tolga_Komp.pdf"]}
+{"year":"2022","title":"How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation?","authors":["A Araabi, C Monz, V Niculae - arXiv preprint arXiv:2208.05225, 2022"],"snippet":"Neural Machine Translation (NMT) is an open vocabulary problem. As a result, dealing with the words not occurring during training (aka out-of-vocabulary (OOV) words) have long been a fundamental challenge for NMT systems. The predominant …","url":["https://arxiv.org/pdf/2208.05225"]}
+{"year":"2022","title":"How good can an automatic translation of Pokémon names be?","authors":["L Talec-Bernarda - Proceedings of the Working Notes of CLEF, 2022"],"snippet":"For those of you who are not familiar with the successful franchise of Pokémon, it revolves around imaginary creatures often representing animals mixed with objects, plants, etc. Their names reflect these characteristics and are, most of the time …","url":["http://ceur-ws.org/Vol-3180/paper-145.pdf"]}
+{"year":"2022","title":"How Using a Foreign Language Influences Perceived Fairness","authors":["G Yu-Buck, A Mishra, H Mishra - ACR North American Advances, 2021"],"snippet":"… We used pre-trained word embedding vectors that were trained with the fastText algorithm and the Common Crawl corpus. The association between the fairness construct and each review is the dependent variable. We followed the procedure of …","url":["https://www.acrwebsite.org/volumes/v49/acr_vol49_3001028.pdf"]}
+{"year":"2022","title":"HTML Violations and Where to Find Them: A Longitudinal Analysis of Specification Violations in HTML","authors":["F Hantke, B Stock - 2022"],"snippet":"… To this end, we identify securityrelevant violations and leverage Common Crawl to check archived pages for these. Using this framework, we automatically analyze over 23K popular domains over time. This analysis reveals that while the number of …","url":["https://swag.cispa.saarland/papers/hantke2022violations.pdf"]}
+{"year":"2022","title":"Human Behavior in Domestic Environments: Prediction and Applications","authors":["S Zehtabian - 2021"],"snippet":"… However, many deep learning algorithms work best under big data regimes, where the number of data samples is counted from the tens of thousands (eg the MNIST dataset) to 500 billion (the Common Crawl dataset used to train the GPT-3 …","url":["https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1944&context=etd2020"]}
+{"year":"2022","title":"Human-Guided Generation of Sketches and Prototypes","authors":["ZF Huang - 2022"],"snippet":"Sketching and prototyping are central to creative activities that improve and advance many aspects of human lives. They enable non-experts to express themselves through drawing, or help User Interface (UI) designers explore diverse alternatives …","url":["https://escholarship.org/content/qt7tq101kp/qt7tq101kp.pdf"]}
+{"year":"2022","title":"HUMAN-INSPIRED COMPUTER VISION & REASONING","authors":["HJ Yi, J Tang, LJ Yu, WM Xuan"],"snippet":"… We used 300-dimensional GloVe vectors for the word embedding layer, which are pre-trained on the Common Crawl corpus consisting of 840B tokens and a 2.2M words vocabulary list [6]. GloVe vectors act as a non-trainable base to learn …","url":["https://www.dsta.gov.sg/ydsp/projects/pdf/research/reports/human-inspired-computer-vision-reasoning.pdf"]}
+{"year":"2022","title":"HW-TSC's Submissions to the WMT 2022 General Machine Translation Shared Task","authors":["D Wei, Z Rao, Z Wu, S Li, Y Luo, Y Xie, X Chen… - Proceedings of the Seventh …, 2022"],"snippet":"… It should be noted that in order to obtain better performance in the general domain, we mix the monolingual data from Common Crawl and News Crawl. … On En→Ru, after the Common Crawl monolingual is added, we observe 2.0 BLEU improvement …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.36.pdf"]}
+{"year":"2022","title":"Hybrid Architecture Based Intelligent Diagnosis Assistant for GP","authors":["R Wang, K Jayathunge, R Page, H Li, J Zhang, X Yang - Authorea Preprints, 2022"],"snippet":"… As mentioned in the introduction part, there mainly four pre-trained word embedding models, because of the wide coverage of different semantic lexical, the ‘crawl-300d-2M.vec’[29] (2-millionword vectors trained on Common Crawl (600B tokens)) of the Google’s …","url":["https://www.authorea.com/doi/pdf/10.22541/au.166741827.78885041"]}
+{"year":"2022","title":"Hypernymy Detection for Low-resource Languages: A Study for Hindi, Bengali, and Amharic","authors":["A Jana, G Venkatesh, SM Yimam, C Biemann - Transactions on Asian and Low …, 2022"],"snippet":"… Even though the focus of our study is not claiming superiority of the distributional semantic models over fastText, given that DT embeddings are prepared from a smaller corpus as compared to the corpus (Wikipedia, Common Crawl) on which …","url":["https://dl.acm.org/doi/abs/10.1145/3490389"]}
+{"year":"2022","title":"HyperTree Proof Search for Neural Theorem Proving","authors":["G Lample, MA Lachaux, T Lavril, X Martinet, A Hayat… - arXiv preprint arXiv …, 2022"],"snippet":"We propose an online training procedure for a transformer-based automated theorem prover. Our approach leverages a new search algorithm, HyperTree Proof Search (HTPS), inspired by the recent success of AlphaZero. Our model learns from …","url":["https://arxiv.org/pdf/2205.11491"]}
+{"year":"2022","title":"iCAR: Bridging Image Classification and Image-text Alignment for Visual Recognition","authors":["Y Wei, Y Cao, Z Zhang, Z Yao, Z Xie, H Hu, B Guo - arXiv preprint arXiv:2204.10760, 2022"],"snippet":"… It extracts image-caption pairs in random web pages crawled between 2014 and 2021 from the Common Crawl web data, and de-noises the dataset by scoring and filtering numerous raw pairs with a threshold using a CLIP ViT-B/32 [40] model …","url":["https://arxiv.org/pdf/2204.10760"]}
+{"year":"2022","title":"iCompass at CheckThat! 2022: ARBERT and AraBERT for Arabic Checkworthy Tweet Identification","authors":["B Taboubi, MAB Nessir, H Haddad - 2022"],"snippet":"This paper provides a detailed overview of systems and its achieved results, which were produced as part of CLEF2022-Check-That! Lab Fighting the COVID-19 Infodemic and Fake News Detection. The task was carried out using transformers pre-trained …","url":["http://ceur-ws.org/Vol-3180/paper-57.pdf"]}
+{"year":"2022","title":"Idea Mining From Online Reviews Using Transformation-Based Natural Language Processing Tasks","authors":["HF Mahdi, LK Gupta, T Choudhury, N Bansal - 2022 International Symposium on …, 2022"],"snippet":"Product reviews from online communities are good sources to innovative ideas. Making use of this unstructured data from these reviews is a complicated process. The major task of identifying good ideas is ensuring the correct reviews are picked …","url":["https://ieeexplore.ieee.org/abstract/document/9932785/"]}
+{"year":"2022","title":"Identifying Implicitly Abusive Remarks about Identity Groups using a Linguistically Informed Approach","authors":["M Wiegand, E Eder, J Ruppenhofer - Proceedings of the 2022 Conference of the …, 2022"],"snippet":"… regression classifier where each verb was represented by its (publicly available) word embedding induced on Common Crawl (Mikolov et al.… As features, we represented each verb by its word embedding from Common Crawl. (Using such a …","url":["https://aclanthology.org/2022.naacl-main.410.pdf"]}
+{"year":"2022","title":"Identifying Opinion Based Questions in Developer Chat Communication","authors":["K Muthu Subash - 2022"],"snippet":"… We have used a general GloVe [108] that uses a common crawl with 42B tokens, 1.9M vocabulary, and 300− dimensional vectors. GloVe Twitter [108] was a common crawl with 27B tokens, 1.2M vocabulary, and 200− dimensional vectors. We have …","url":["https://curve.carleton.ca/system/files/etd/c1f5bab8-ffe1-4dfc-9dd9-5850a5ad1bd7/etd_pdf/91899acd83d9b05a969f14e6a14dfa0a/muthusubash-identifyingopinionbasedquestionsindeveloper.pdf"]}
+{"year":"2022","title":"IDEOLOGY DETECTION USING TRANSFORMER-BASED MACHINE LEARNING MODELS","authors":["O ÖZTÜRK, A ÖZCAN"],"snippet":"Ideology detection has been a challenging but essential problem that has been studied for a long time. Certain groups and organizations, such as politicians, rely on people’s political views to make wise or forward-looking decisions. In the previous …","url":["https://www.researchgate.net/profile/Oktay-Ozturk-3/publication/357660800_Ideology_Detection_Using_Transformer-Based_Machine_Learning_Models/links/61d87712e669ee0f5c8f1b97/Ideology-Detection-Using-Transformer-Based-Machine-Learning-Models.pdf"]}
+{"year":"2022","title":"IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehension","authors":["RA Putri, A Oh - arXiv preprint arXiv:2210.13778, 2022"],"snippet":"… These language models are mostly pre-trained on the common-crawl dataset, which may contain harmful biases or stereotypes. All datasets in this work are publicly available and distributed under CC BY-SA 4.0 license. Our data collection …","url":["https://arxiv.org/pdf/2210.13778"]}
+{"year":"2022","title":"IELM: An Open Information Extraction Benchmark for Pre-Trained Language Models","authors":["C Wang, X Liu, D Song - arXiv preprint arXiv:2210.14128, 2022"],"snippet":"We introduce a new open information extraction (OIE) benchmark for pre-trained language models (LM). Recent studies have demonstrated that pre-trained LMs, such as BERT and GPT, may store linguistic and relational knowledge. In particular …","url":["https://arxiv.org/pdf/2210.14128"]}
+{"year":"2022","title":"IgboBERT Models: Building and Training Transformer Models for the Igbo Language","authors":["C Chukwuneke, I Ezeani, P Rayson, M El-Haj"],"snippet":"This work presents a standard Igbo named entity recognition (IgboNER) dataset as well as the results from training and fine-tuning state-of-the-art transformer IgboNER models. We discuss the process of our dataset creation-data collection and …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.547.pdf"]}
+{"year":"2022","title":"IIT Bombay's WMT22 Automatic Post-Editing Shared Task Submission","authors":["S Deoghare, P Bhattacharyya"],"snippet":"This paper describes IIT Bombay’s submission to the WMT-22 Automatic Post-Editing (APE) shared task for the English-Marathi (En-Mr) language pair. We follow the curriculum training strategy to train our APE system. First, we train an encoder-decoder …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.67.pdf"]}
+{"year":"2022","title":"Image Captioning for Thai Cultures","authors":["S Watcharabutsarakham, S Marukatat… - 2022 17th International Joint …, 2022"],"snippet":"Before each trip, tourists generally gather information or photos from different places. This work aims at providing additional information about touristic sites in Thailand via automatic image captioning. Image captioning is the process of generating a …","url":["https://ieeexplore.ieee.org/abstract/document/9960251/"]}
+{"year":"2022","title":"Imbalanced data as risk factor of discriminating automated decisions","authors":["A Vetrò - 2021"],"snippet":"… experiment on the search engine Common Crawl [17]. The authors compared three techniques of machine learning for occupational classification with almost 400.000 collected biographies. In all cases, even without explicitly using gender …","url":["https://www.jipitec.eu/issues/jipitec-12-4-2021/5452/vetro_pdf.pdf"]}
+{"year":"2022","title":"Impact of convolutional neural network and FastText embedding on text classification","authors":["M Umer, Z Imtiaz, M Ahmad, M Nappi, C Medaglia… - Multimedia Tools and …, 2022"],"snippet":"… It contains 2 million common crawl words with 300 −dimensions, providing 600 billion word-vectors. It uses hand-crafted n-grams as features in addition to single words. Text classification is performed very effectively and efficiently because of its …","url":["https://link.springer.com/article/10.1007/s11042-022-13459-x"]}
+{"year":"2022","title":"Impact of preprocessing and word embedding on extreme multi-label patent classification tasks","authors":["G Jung, J Shin, S Lee - Applied Intelligence, 2022"],"snippet":"… The Word2Vec pre-trained model learned approximately 3 million words using GoogleNews as a dataset, whereas the GloVe pre-trained model learned approximately 2.2 million words using the Common Crawl dataset [30, 31]. Because …","url":["https://link.springer.com/article/10.1007/s10489-022-03655-5"]}
+{"year":"2022","title":"Impact of Pretraining Term Frequencies on Few-Shot Reasoning","authors":["Y Razeghi, RL Logan IV, M Gardner, S Singh - arXiv preprint arXiv:2202.07206, 2022"],"snippet":"Pretrained Language Models (LMs) have demonstrated ability to perform numerical reasoning by extrapolating from a few examples in few-shot settings. However, the extent to which this extrapolation relies on robust reasoning is unclear. In this paper …","url":["https://arxiv.org/pdf/2202.07206"]}
+{"year":"2022","title":"Impact of Sentence Representation Matching in Neural Machine Translation","authors":["H Jung, K Kim, JH Shin, SH Na, S Jung, S Woo - Applied Sciences, 2022"],"snippet":"… To build a training set, we merged the Europarl parallel corpus and the Common-crawl corpus released from WMT-14 (http://www.statmt.org/wmt14/, accessed on 18 January 2022). We applied tokenizing and lowercasing and limited the length of …","url":["https://www.mdpi.com/2076-3417/12/3/1313/pdf"]}
+{"year":"2022","title":"Impact of Tokenization on Language Models: An Analysis for Turkish","authors":["C Toraman, EH Yilmaz, F Şahinuç, O Ozcelik - arXiv preprint arXiv:2204.08832, 2022"],"snippet":"… OSCAR is a multilingual corpus that is obtained by filtering of the Common Crawl corpus that maintain an open repository of publicly available web pages. We use the split of this corpus prepared for Turkish. However, we observe that this split includes …","url":["https://arxiv.org/pdf/2204.08832"]}
+{"year":"2022","title":"Implementación de algoritmos de reducción de sesgo en WEFE","authors":["MJ Zambrano Burrows - 2022"],"snippet":"Se ha demostrado en los últimos años que los modelos de word embeddings logran captar los sesgos presentes en los corpus de los que son entrenados, aprendiendo relaciones con estereotipos de género, raciales, entre otros. A modo de abordar el …","url":["https://repositorio.uchile.cl/bitstream/handle/2250/188824/Implementacion-de-algoritmos-de-reduccion-de-sesgo-en-WEFE.pdf?sequence=1"]}
+{"year":"2022","title":"Implicit Social Cognition","authors":["B Kurdi, MR Banaji"],"snippet":"Among the central features of the mind that drive social behavior are the attitudes and beliefs that humans bring to their engagement with other humans. Accordingly, ever since the inception of the field, research in social psychology has been guided …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=wD90EAAAQBAJ&oi=fnd&pg=PA323&dq=commoncrawl&ots=cFuiqkafcD&sig=PPJezjT4cihMsBdiO_1wITIQ09w"]}
+{"year":"2022","title":"Improved Zero-Shot Audio Tagging & Classification with Patchout Spectrogram Transformers","authors":["P Primus, G Widmer - arXiv preprint arXiv:2208.11402, 2022"],"snippet":"… We choose Word2Vec and Glove models that are pre-trained on the Google News and the Common Crawl dataset, respectively. Both produce embedding vectors of size 300. To embed textual labels made out of multiple words (eg, fire truck) …","url":["https://arxiv.org/pdf/2208.11402"]}
+{"year":"2022","title":"Improving Address Sequence Tagger Using Geographical Context","authors":["L Eriksson, M Olsson"],"snippet":"For humans, parsing an address into its components such as street and city is easy but time-consuming. Computers can have a harder time with such tasks. There are existing tools that use machine learning which has proven to be effective but still …","url":["https://lup.lub.lu.se/student-papers/record/9085667/file/9085668.pdf"]}
+{"year":"2022","title":"Improving BERTScore for Machine Translation Evaluation Through Contrastive Learning","authors":["O Yousuf - 2022"],"snippet":"… Scaled to one hundred languages, XLM-RoBERTa was pre-trained on 2.5TB of filtered CommonCrawl data (CC-100). However, it is … Furthermore, quality of data also poses challenges, as CommonCrawl or parallel localization data from projects …","url":["https://www.diva-portal.org/smash/get/diva2:1671848/FULLTEXT01.pdf"]}
+{"year":"2022","title":"Improving Bilingual Lexicon Induction with Cross-Encoder Reranking","authors":["Y Li, F Liu, I Vulić, A Korhonen - arXiv preprint arXiv:2210.16953, 2022"],"snippet":"… Panlex-BLI does not provide processed WEs, so we follow the original instructions from the authors and adopt fastText WEs trained on Common Crawl + Wikipedia.The WEs are trimmed to the most frequent 200k words for each language …","url":["https://arxiv.org/pdf/2210.16953"]}
+{"year":"2022","title":"Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles","authors":["S Ye, Y Xie, D Chen, Y Xu, L Yuan, C Zhu, J Liao - arXiv preprint arXiv:2211.16504, 2022"],"snippet":"This paper focuses on analyzing and improving the commonsense ability of recent popular vision-language (VL) models. Despite the great success, we observe that existing VL-models still lack commonsense knowledge/reasoning ability (eg, \"Lemons …","url":["https://arxiv.org/pdf/2211.16504"]}
+{"year":"2022","title":"Improving Domain-specific Cross-lingual Embeddings with Automatically Generated Bilingual Dictionaries","authors":["P Singh, AR Terryn, E Lefever - Computational Linguistics in the Netherlands Journal, 2022"],"snippet":"… To investigate this, we trained a set of FastText embeddings in English, initialised using the same Common Crawl and Wikipedia … Since the PubMed data would be vastly different from the Common Crawl and Wikipedia corpora, we can assume this …","url":["https://clinjournal.org/clinj/article/download/151/159"]}
+{"year":"2022","title":"Improving End-to-end Speech Translation by Leveraging Auxiliary Speech and Text Data","authors":["Y Zhang, C Xu, B Hu, C Zhang, T Xiao, J Zhu - arXiv preprint arXiv:2212.01778, 2022"],"snippet":"We present a method for introducing a text encoder into pre-trained end-to-end speech translation systems. It enhances the ability of adapting one modality (ie, source-language speech) to another (ie, source-language text). Thus, the speech …","url":["https://arxiv.org/pdf/2212.01778"]}
+{"year":"2022","title":"Improving Language Model Predictions via Prompts Enriched with Knowledge Graphs","authors":["R Brate, MH Dang, F Hoppe, Y He, A Meroño-Peñuela… - Workshop on Deep …, 2022"],"snippet":"… These entities are embedded in HTML pages on the web using Microformat, Microdata and RDFa from the Common Crawl web corpus, the largest and most up-to-date data web corpus available to the public. As more and more websites embed …","url":["https://www.fiz-karlsruhe.de/sites/default/files/FIZ/Dokumente/Forschung/ISE/Publications/Conferences-Workshops/Improving-Language-Model-Predictions-via_Prompts-Enriched-with-Knowledge-Graphs-HOPPE-DL4KG%40ISWC2022.pdf"]}
+{"year":"2022","title":"Improving Neural Question Answering with Retrieval and Generation","authors":["PSH Lewis - 2022"],"snippet":"Text-based Question Answering (QA) is a subject of interest both for its practical applications, and as a test-bed to measure the key Artificial Intelligence competencies of Natural Language Processing (NLP) and the representation and …","url":["https://discovery.ucl.ac.uk/id/eprint/10151750/2/Patrick_Lewis_Thesis__for_submission_to_UCL_.pdf"]}
+{"year":"2022","title":"Improving open text matching in a communication serious game","authors":["A Ungureanu - 2022"],"snippet":"… The ”clips/mfaq” model I am using for this application is pretrained on the ”MFAQ” [21] dataset, which is a multilingual corpus of Frequently Asked Questions parsed from the Common CrawlCommon Crawl is an open-source database of web crawling …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/43284/Andrei_Ungureanu_Master_Thesis.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Improving searchability of datasets","authors":["E Kacprzak - 2022"],"snippet":"Data is one of the most important digital assets in the world thanks to its business and social value. As is becoming increasingly available online, in order to use it effectively, we need tools that allow us to retrieve the most relevant datasets that …","url":["https://eprints.soton.ac.uk/457260/1/Emilia_Kacprzak_PhD_WAIS_27_March.pdf"]}
+{"year":"2022","title":"Improving Sentiment Analysis By Emotion Lexicon Approach on Vietnamese Texts","authors":["AL Doan, ST Luu - arXiv preprint arXiv:2210.02063, 2022"],"snippet":"The sentiment analysis task has various applications in practice. In the sentiment analysis task, words and phrases that represent positive and negative emotions are important. Finding out the words that represent the emotion from the text can …","url":["https://web7.arxiv.org/pdf/2210.02063"]}
+{"year":"2022","title":"Improving Short Text Classification With Augmented Data Using GPT-3","authors":["S Balkus, D Yan - arXiv preprint arXiv:2205.10981, 2022"],"snippet":"GPT-3 is a large-scale natural language model developed by OpenAI that can perform many different tasks, including topic classification. Although researchers claim that it requires only a small number of in-context examples to learn a task, in …","url":["https://arxiv.org/pdf/2205.10981"]}
+{"year":"2022","title":"Improving Taxonomy-based Categorization with Categorical Graph Neural Networks","authors":["T Du, K Chang, P Liu, R Zhang - 2021 IEEE International Conference on Big Data …, 2021"],"snippet":"… Then each query was converted to a 300-dimensional embedding by averaging each word’s FastText embedding [23] (pretrained on the common-crawl dataset). Each FastText word embedding was L2 normalized before use. The query …","url":["https://ieeexplore.ieee.org/abstract/document/9671372/"]}
+{"year":"2022","title":"Improving the Accessibility of Arabic Electronic Theses and Dissertations (ETDs) with Metadata and Classification","authors":["E Abdelrahman - 2021"],"snippet":"Much research work has been done to extract data from scientific papers, journals, and articles. However, Electronic Theses and Dissertations (ETDs) remain an unexplored genre of data in the research fields of natural language processing and …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/107790/Abdelrahman_E_T_2021.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Improving the Robustness of Summarization Models by Detecting and Removing Input Noise","authors":["K Krishna, Y Zhao, J Ren, B Lakshminarayanan, J Luo… - arXiv preprint arXiv …, 2022"],"snippet":"The evaluation of abstractive summarization models typically uses test data that is identically distributed as training data. In real-world practice, documents to be summarized may contain input noise caused by text extraction artifacts or data …","url":["https://arxiv.org/pdf/2212.09928"]}
+{"year":"2022","title":"Improving Word Translation via Two-Stage Contrastive Learning","authors":["Y Li, F Liu, N Collier, A Korhonen, I Vulić - arXiv preprint arXiv:2203.08307, 2022"],"snippet":"Word translation or bilingual lexicon induction (BLI) is a key cross-lingual task, aiming to bridge the lexical gap between different languages. In this work, we propose a robust and effective two-stage contrastive learning framework for the BLI …","url":["https://arxiv.org/pdf/2203.08307"]}
+{"year":"2022","title":"In Situ Answer Sentence Selection at Web-scale","authors":["Z Zhang, T Vu, A Moschitti - arXiv preprint arXiv:2201.05984, 2022"],"snippet":"… Question Sampling We sample the questions from a large collection of information inquiries collected from Web data, eg, CommonCrawl. … The candidates are extracted from 30MM passages, retrieved from a large index having …","url":["https://arxiv.org/pdf/2201.05984"]}
+{"year":"2022","title":"In-context Examples Selection for Machine Translation","authors":["S Agrawal, C Zhou, M Lewis, L Zettlemoyer… - arXiv preprint arXiv …, 2022"],"snippet":"… As XGLM is trained on monolingual Common Crawl snapshots, translation in any domain and language could be considered an out-of-domain task from the model’s perspective. However, we hypothesize that translation in specific domains like …","url":["https://arxiv.org/pdf/2212.02437"]}
+{"year":"2022","title":"INAUGURAL ARTICLE by a Recently Elected Academy Member: When danger strikes: A linguistic tool for tracking America's collective response to threats","authors":["VK Choi, S Shrestha, X Pan, MJ Gelfand - Proceedings of the National Academy of …, 2022"],"snippet":"In today’s vast digital landscape, people are constantly exposed to threatening language, which attracts attention and activates the human brain’s fear circuitry. However, to date, we have lacked the tools needed to identify threatening language …","url":["https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8795557/"]}
+{"year":"2022","title":"IndicXNLI: Evaluating Multilingual Inference for Indian Languages","authors":["D Aggarwal, V Gupta, A Kunchukuttan - arXiv preprint arXiv:2204.08776, 2022"],"snippet":"… XLM-RoBERTa is pre-trained using the common crawl monolingual data. mBERT (cased/uncased) includes pre-training on nine of eleven Indic lan… These model use the Indic enrich monolingual corpora: Common Crawl, Oscar and IndicCorp and …","url":["https://arxiv.org/pdf/2204.08776"]}
+{"year":"2022","title":"IndicXTREME: A Multi-Task Benchmark For Evaluating Indic Languages","authors":["S Doddapaneni, R Aralikatte, G Ramesh, S Goyal… - arXiv preprint arXiv …, 2022"],"snippet":"In this work, we introduce IndicXTREME, a benchmark consisting of nine diverse tasks covering 18 languages from the Indic sub-continent belonging to four different families. Across languages and tasks, IndicXTREME contains a total of 103 …","url":["https://arxiv.org/pdf/2212.05409"]}
+{"year":"2022","title":"Indonesian Hoax News Classification with Multilingual Transformer Model and BERTopic","authors":["LB Hutama, D Suhartono - Informatica, 2022"],"snippet":"… The most prominent development of the XLM-R model lies in the size of the dataset used where XLM-R is trained using 2.5TB of Common Crawl data in 100 languages, making the XLM-R model superior to previous multi-language models …","url":["https://www.informatica.si/index.php/informatica/article/viewFile/4336/1920"]}
+{"year":"2022","title":"InfoDCL: A Distantly Supervised Contrastive Learning Framework for Social Meaning","authors":["C Zhang, M Abdul-Mageed, G Jawahar - arXiv preprint arXiv:2203.07648, 2022"],"snippet":"Existing supervised contrastive learning frameworks suffer from two major drawbacks: (i) they depend on labeled data, which is limited for the majority of tasks in real-world, and (ii) they incorporate inter-class relationships based on instance-level information …","url":["https://arxiv.org/pdf/2203.07648"]}
+{"year":"2022","title":"Inria-ALMAnaCH at the WMT 2022 shared task: Does Transcription Help Cross-Script Machine Translation?","authors":["JO Alabi, L Nishimwe, B Muller, C Rey, B Sagot… - Proceedings of the Seventh …, 2022"],"snippet":"This paper describes the Inria ALMAnaCH team submission to the WMT 2022 general translation shared task. Participating in the language directions {cs,ru,uk}→en and cs↔uk, we experiment with the use of a dedicated Latin-script transcription …","url":["https://hal.inria.fr/hal-03836180/document"]}
+{"year":"2022","title":"Insights from heterogeneous data through transitive semantic relationships and text analytics","authors":["D Ralph - 2022"],"snippet":"Many organisations are finding that the volume of information they need to analyse to make effective decisions is increasing. An important element in effective decision making is the ability to prioritise information quickly and accurately from a variety of …","url":["https://eprints.soton.ac.uk/470732/1/David_Ralph_PhD_Thesis.pdf"]}
+{"year":"2022","title":"Instance-Specific Feature Propagation for Referring Segmentation","authors":["C Liu, X Jiang, H Ding - IEEE Transactions on Multimedia, 2022"],"snippet":"… We follow prior work [12], [36] and adopt the GloVe word embeddings [32] on Common Crawl 840B tokens. We use Adam with the base learning rate of 0.001 for optimization. Images are resized to 416 × 416 before sending to the network, and …","url":["https://ieeexplore.ieee.org/abstract/document/9745353/"]}
+{"year":"2022","title":"Integrating character-level and word-level representation for affect in Arabic tweets","authors":["AI Alharbi, P Smith, M Lee - Data & Knowledge Engineering, 2022"],"snippet":"Affect tasks, which range from sentiment polarity classification to finer grained sentiment strength and emotional intensity detection, have become of increasing interest due to the vast amount of user-generated content and advanced learning …","url":["https://www.sciencedirect.com/science/article/pii/S0169023X21000938"]}
+{"year":"2022","title":"Integrating Product Data using Deep Learning","authors":["R Peeters, C Bizer - Proceedings of the 7th bwHPC Symposium, 2022"],"snippet":"… A successful approach for dealing with the heterogeneity of product offers is to combine deep learning-based matching techniques with large amounts of training data which can be extracted from Web corpora such as the Common Crawl. Training …","url":["https://oparu.uni-ulm.de/xmlui/bitstream/handle/123456789/46143/bwHPC7_11.pdf?sequence=1"]}
+{"year":"2022","title":"Intelligent Techniques to Accelerate Everyday Text Communication","authors":["JK Adhikary - 2022"],"snippet":"People with some form of speech-or motor-impairments usually use a high-tech augmentative and alternative communication (AAC) device to communicate with other people in writing or in face-to-face conversations. Their text entry rate on these …","url":["https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=2550&context=etdr"]}
+{"year":"2022","title":"Interactive capsule network for implicit sentiment analysis","authors":["Y Qian, J Wang, D Li, X Zhang - Applied Intelligence, 2022"],"snippet":"Existing sentiment analysis models mainly rely on evident emotive words within phrases. When the apparent emotional words within phrases are eliminated, the performance of these models will inevitably decrease. The implicit communication of …","url":["https://link.springer.com/article/10.1007/s10489-022-03584-3"]}
+{"year":"2022","title":"Interactive Question Answering","authors":["E Toledo"],"snippet":"Artificial intelligence has long aspired to create systems that can perform real-world activities and converse with humans using natural language. In the pursuit of this goal, Interactive Question Answering was proposed. Specifically for language …","url":["https://showcase.sit.uct.ac.za/static/media/122/9ed8c65d-3e35-43d9-86ab-acd83c3abb7c.pdf"]}
+{"year":"2022","title":"International Journal of Knowledge Processing Studies","authors":["SS Moosavi, S Ciruskabiri, A Varnaseri"],"snippet":"The speed and ease of production and loading of content on the web, the exponential increase in the volume and short life cycle of data in this space, have made the processes of collection, refinement, organization, storage, management …","url":["http://kps.artahub.ir/article_152778_d3fab5eab308c5bb383c1a874e0354d4.pdf"]}
+{"year":"2022","title":"Internet-augmented language models through few-shot prompting for open-domain question answering","authors":["A Lazaridou, E Gribovskaya, W Stokowiec, N Grigorev - arXiv preprint arXiv …, 2022"],"snippet":"In this work, we aim to capitalize on the unique few-shot capabilities offered by large-scale language models to overcome some of their challenges with respect to grounding to factual and up-to-date information. Motivated by semi-parametric language models …","url":["https://arxiv.org/pdf/2203.05115"]}
+{"year":"2022","title":"Interpreting Arabic Transformer Models","authors":["A Abdelali, N Durrani, F Dalvi, H Sajjad - arXiv preprint arXiv:2201.07434, 2022"],"snippet":"Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While these models have been compared with …","url":["https://arxiv.org/pdf/2201.07434"]}
+{"year":"2022","title":"Interpreting Logical Metonymy through Dense Paraphrasing","authors":["B Ye, J Tu, E Jezek, J Pustejovsky - Proceedings of the Annual Meeting of the …, 2022"],"snippet":"… The extensive usage of C4 and the nature of it being sourced from the public Common Crawl web scrape ensure its huge volume and various language styles compared to other public datasets, which provides a “real world” text distribution for our task. …","url":["https://escholarship.org/content/qt19k4w0c1/qt19k4w0c1.pdf"]}
+{"year":"2022","title":"Interpreting mental state decoding with deep learning models","authors":["AW Thomas, C Ré, RA Poldrack - Trends in Cognitive Sciences, 2022"],"snippet":"In mental state decoding, researchers aim to identify the set of mental states (eg, experiencing happiness or fear) that can be reliably identified from the activity patterns of a brain region (or network). Deep learning (DL) models are highly …","url":["https://www.sciencedirect.com/science/article/pii/S1364661322001607"]}
+{"year":"2022","title":"Introducing EM-FT for Manipuri-English Neural Machine Translation","authors":["R Huidrom, Y Lepage"],"snippet":"This paper introduces pretrained word embeddings for Manipuri, a low-resourced Indian language. The pretrained word embeddings based on fastText is capable of handling the highly agglutinative language Manipuri (mni). We then perform …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/WILDRE6/pdf/2022.wildre6-1.1.pdf"]}
+{"year":"2022","title":"Introduction to Language Models","authors":["SM Jain - Introduction to Transformers for NLP, 2022"],"snippet":"… It was trained using the largest corpus a model has ever been trained on, which is known as the Common Crawl , and it has 175 billion different parameters. This is made possible in part by the semi-supervised training method of a language model …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-8844-3_1"]}
+{"year":"2022","title":"Intrusion detection based on keystroke biometrics and siamese neural networks","authors":["A Budžys, O Kurasova, V Medvedev - DAMSS: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148178661/148178661.pdf"]}
+{"year":"2022","title":"Investigating language relationships in multilingual sentence encoders through the lens of linguistic typology","authors":["R Choenni, E Shutova - Computational Linguistics, 2022"],"snippet":"Multilingual sentence encoders have seen much success in cross-lingual model transfer for downstream NLP tasks. The success of this transfer is, however, dependent on the model’s ability to encode the patterns of cross-lingual similarity …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00444/2008428/coli_a_00444.pdf"]}
+{"year":"2022","title":"Investigating Opinions on Public Policies in Digital Media: Setting up a Supervised Machine Learning Tool for Stance Classification","authors":["C Viehmann, T Beck, M Maurer, O Quiring, I Gurevych - Communication Methods and …, 2022"],"snippet":"Supervised machine learning (SML) provides us with tools to efficiently scrutinize large corpora of communication texts. Yet, setting up such a tool involves plenty of decisions starting with the data needed for training, the selection of an algorithm …","url":["https://www.tandfonline.com/doi/abs/10.1080/19312458.2022.2151579"]}
+{"year":"2022","title":"Investigating the Country of Origin and the Role of the. eu TLD in External Trade of European Union Member States","authors":["A Giannakoulopoulos, M Pergantis, L Limniati… - Future Internet, 2022"],"snippet":"… that queried the Common Crawl Index servers for Web pages and collected all the unique domains found. Common Crawl is a non-profit foundation providing access to web information through an open database of web crawl data [28]. The …","url":["https://www.mdpi.com/1999-5903/14/6/174/pdf?version=1654339602"]}
+{"year":"2022","title":"Investigating the Efficient Use of Word Embedding with Neural-Topic Models for Interpretable Topics from Short Texts","authors":["R Murakami, B Chakraborty - Sensors, 2022"],"snippet":"With the rapid proliferation of social networking sites (SNS), automatic topic extraction from various text messages posted on SNS are becoming an important source of information for understanding current social trends or needs. Latent …","url":["https://www.mdpi.com/1424-8220/22/3/852/pdf"]}
+{"year":"2022","title":"Investigating the Quality of Static Anchor Embeddings from Transformers for Under-Resourced Languages","authors":["P Singh, O De Clercq, E Lefever - The 1st Annual Meeting of the ELRA/ISCA Special …, 2022"],"snippet":"… This problem could be solved by adding more monolingual data (from Common Crawl, for example) for the anchor extraction step. We also … Since most methodologies use the Wikipedia and/or the Common Crawl corpus as initial pre-training …","url":["https://biblio.ugent.be/publication/8759657/file/8759658.pdf"]}
+{"year":"2022","title":"Investigations of Performance and Bias in Human-AI Teamwork in Hiring","authors":["A Peng, B Nushi, E Kiciman, K Inkpen, E Kamar - arXiv preprint arXiv:2202.11812, 2022"],"snippet":"In AI-assisted decision-making, effective hybrid (human-AI) teamwork is not solely dependent on AI performance alone, but also on its impact on human decision-making. While prior work studies the effects of model accuracy on humans, we endeavour …","url":["https://arxiv.org/pdf/2202.11812"]}
+{"year":"2022","title":"Is It Out Yet? Automatic Future Product Releases Extraction from Web Data","authors":["G Fuchs, I Ben-Shaul, M Mandelbrod"],"snippet":"… As each monthly snapshot of the Common Crawl data may include hundreds of millions of web pages, we have decided to use a simple heuristics to select web pages which discuss future product releases. Our approach is based on manually curating …","url":["https://ebay.co.il/wp-content/uploads/2022/12/Is-It-Out-Yet-Automatic-Future-Product-Releases-Extraction-from-Web-Data.pdf"]}
+{"year":"2022","title":"Is this Question Real? Dataset Collection on Perceived Intentions and Implicit Attack Detection","authors":["MS Mirzaei, K Meshgi, S Sekine - Proceedings of the ACM Web Conference 2022, 2022"],"snippet":"… We used GloVe [38] word embedding (300d version on 840B Common Crawl data) for obtaining vector representations for words and Xavier initialization for the parameters. The batch size is set to 32, and the loss is calculated using binary cross-entropy …","url":["https://dl.acm.org/doi/abs/10.1145/3485447.3512005"]}
+{"year":"2022","title":"Is Using an AI to Simplify a Scientific Text Really Worth It","authors":["TB Talec-Bernard - Proceedings of the Working Notes of CLEF, 2022"],"snippet":"Nowadays, we encounter Artificial Intelligence (AI) everywhere and although it can help us save a lot of time when performing certain tasks such as translating or correcting a text, it can also lead to a loss in quality. When it comes to automatically …","url":["http://ceur-ws.org/Vol-3180/paper-245.pdf"]}
+{"year":"2022","title":"Isomorphic Cross-lingual Embeddings for Low-Resource Languages","authors":["S Sannigrahi, J Read - arXiv preprint arXiv:2203.14632, 2022"],"snippet":"… 2018) which uses Wikipedia dumps and Common Crawl for all languages. In addition to this, we use available parallel data between the following related language pairs respectively: English-Hindi (hi) for Nepali, English-Estonian (et) for …","url":["https://arxiv.org/pdf/2203.14632"]}
+{"year":"2022","title":"IsoVec: Controlling the Relative Isomorphism of Word Embedding Spaces","authors":["K Marchisio, N Verma, K Duh, P Koehn - arXiv preprint arXiv:2210.05098, 2022"],"snippet":"The ability to extract high-quality translation dictionaries from monolingual word embedding spaces depends critically on the geometric similarity of the spaces -- their degree of \"isomorphism.\" We address the root-cause of faulty cross-lingual …","url":["https://arxiv.org/pdf/2210.05098"]}
+{"year":"2022","title":"IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation","authors":["G Sarti, M Nissim - arXiv preprint arXiv:2203.03759, 2022"],"snippet":"… 2020), a large collection including roughly 750GB of webscraped English texts sourced from the CommonCrawl. This was subsequently cleaned employing heuristics aimed at removing templated fillers, text deduplication, Javascript code …","url":["https://arxiv.org/pdf/2203.03759"]}
+{"year":"2022","title":"Jan Chołoniewski, B. Eng., M. Sc.","authors":["JA Hołyst, B Eng, J Sienkiewicz"],"snippet":"W pracy analizujemy i modelujemy działalność internetowych serwisów informacyjnych, łącząc ilościowe podejście medioznawcze z metodami fizyki statystycznej. Głównymi celami prezentowanych badań są:(i) charakterystyka …","url":["https://repo.pw.edu.pl/docstore/download/WUT6177f85542a746fd8ceaa3bc9fc6d8d1/PhD_fizyka_Jan_Choloniewski+do+druku.pdf"]}
+{"year":"2022","title":"Jointly Multi-Similarity Loss for Deep Metric Learning","authors":["L Zhang, S Shen, L Li, H Wang, X Li, J Lang - 2021 IEEE International Conference on …, 2021"],"snippet":"… In particular, all of the input sentences are split and initialized in the word representation layer with the 300-dimensional GloVe word vectors pre-trained from the 840B Common Crawl corpus [24], and the embeddings of the out-of-vocabulary …","url":["https://ieeexplore.ieee.org/abstract/document/9679139/"]}
+{"year":"2022","title":"JParaCrawl v3. 0: A Large-scale English-Japanese Parallel Corpus","authors":["M Morishita, K Chousa, J Suzuki, M Nagata - arXiv preprint arXiv:2202.12607, 2022"],"snippet":"… To list such parallel websites, we analyzed all the Common Crawl text archive data released from March 2019 to August 20213. We identified the language in the archive by CLD24 and listed 100,000 large websites that roughly have the same …","url":["https://arxiv.org/pdf/2202.12607"]}
+{"year":"2022","title":"Just Rank: Rethinking Evaluation with Word and Sentence Similarities","authors":["B Wang, CCJ Kuo, H Li - arXiv preprint arXiv:2203.02679, 2022"],"snippet":"Word and sentence embeddings are useful feature representations in natural language processing. However, intrinsic evaluation for embeddings lags far behind, and there has been no significant update since the past decade. Word and sentence …","url":["https://arxiv.org/pdf/2203.02679"]}
+{"year":"2022","title":"Just-In-Time Obsolete Comment Detection and Update","authors":["Z Liu, X Xia, D Lo, M Yan, S Li - IEEE Transactions on Software Engineering, 2021"],"snippet":"Comments are valuable resources for the development, comprehension and maintenance of software. However, while changing code, developers sometimes neglect the evolution of the corresponding comments, resulting in obsolete …","url":["https://ieeexplore.ieee.org/abstract/document/9664004/"]}
+{"year":"2022","title":"k 𝑘 k italic_k-Nearest Neighbor Augmented Neural Networks for Text Classification","authors":["Z Wang, W Hamza, L Song"],"snippet":"In recent years, many deep-learning based models are proposed for text classification. This kind of models well fits the training set from the statistical point of view. However, it lacks the capacity of utilizing instance-level information from …","url":["https://ar5iv.labs.arxiv.org/html/1708.07863"]}
+{"year":"2022","title":"Keyword Extraction in Scientific Documents","authors":["SX Rao, P Piriyatamwong, P Ghoshal, S Nasirian… - arXiv preprint arXiv …, 2022"],"snippet":"… As an additional hint to participants, document embeddings for each item in the train and test sets, as well as word embeddings for the entire corpus, were generated from a fastText model2 trained on the English Common Crawl dataset (cc.en.300.bin)3. …","url":["https://arxiv.org/pdf/2207.01888"]}
+{"year":"2022","title":"Knowledge Complementarity between Seed Investors and Startup Founders: Lessons from Accelerators","authors":["S Santamaria, S Breschi"],"snippet":"Which entrepreneurs benefit most from accelerator programs? In this paper, we argue that the value-added by startup accelerators depends critically on whether the knowledge these supporting institutions provide is complementary to or a substitute …","url":["https://kid2021.sciencesconf.org/data/program/kid2021_breschi.pdf"]}
+{"year":"2022","title":"Knowledge Distillation Transfer Sets and their Impact on Downstream NLU Tasks","authors":["C Peris, L Tan, T Gueudre, T Gojayev, V Wei, G Oz - arXiv preprint arXiv:2210.04834, 2022"],"snippet":"… We then sample 50K utterances each, from the Wikipedia and Common Crawl data sets of the corresponding language. We create a tf-… CommonCrawl have relatively larger improvement in SemER, when compared to domains that are more …","url":["https://arxiv.org/pdf/2210.04834"]}
+{"year":"2022","title":"Knowledge extraction from fictional texts","authors":["CX Chu - 2022"],"snippet":"Knowledge extraction from text is a key task in natural language processing, which involves many sub-tasks, such as taxonomy induction, named entity recognition and typing, relation extraction, knowledge canonicalization and so on. By constructing …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/32914/1/thesis-twoside-toprint.pdf"]}
+{"year":"2022","title":"Knowledge graph expansion using question answering by leveraging language models","authors":["H Fock - 2022"],"snippet":"… C4 is based on the Common Crawl Web Archive9, a massive collection of web-extracted text, with around 20 TB of text data added each month. The researchers took the massive collection of web-extracted text data with the actuality of April 2019. The …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/42416/MasterThesis_HagenAadFock_1935569_FinalVersion.pdf?sequence=1"]}
+{"year":"2022","title":"KNOWLEDGE REPRESENTATIONS+ SCHEMATA","authors":["LJ Martin"],"snippet":"… Data Source: Common Crawl …","url":["https://interactive-fiction-class.org/slides/CIS700-KnowledgeBases.pdf"]}
+{"year":"2022","title":"Korean and Multilingual Language Models Study for Cross-Lingual Post-Training (XPT)","authors":["S Son, C Park, J Lee, M Shim, C Lee, K Park, H Lim - Journal of the Korea …, 2022"],"snippet":"It has been proven through many previous researches that the pretrained language model with a large corpus helps improve performance in various natural language processing tasks. However, there is a limit to building a large-capacity corpus for …","url":["https://www.koreascience.or.kr/article/JAKO202210459401088.pdf"]}
+{"year":"2022","title":"Kv2vec: A Distributed Representation Method for Key-value Pairs from Metadata Attributes","authors":["C Niu, W Zhang, S Byna, Y Chen - 2022 IEEE High Performance Extreme Computing …, 2022"],"snippet":"… Common Crawl web corpus has the least error rate. Therefore, we choose to use the pre-trained dictionary generated from the word2vec model with Common Crawl … the pre-trained and retrofitted dictionary generated by the word2vec model on the …","url":["https://ieeexplore.ieee.org/abstract/document/9926389/"]}
+{"year":"2022","title":"L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources","authors":["R Joshi - arXiv preprint arXiv:2202.01159, 2022"],"snippet":"We present L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual corpus with 24.8M sentences and 289M tokens. We further present, MahaBERT, MahaAlBERT …","url":["https://arxiv.org/pdf/2202.01159"]}
+{"year":"2022","title":"L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models","authors":["A Velankar, H Patil, A Gore, S Salunke, R Joshi - arXiv preprint arXiv:2203.13778, 2022"],"snippet":"Social media platforms are used by a large number of people prominently to express their thoughts and opinions. However, these platforms have contributed to a substantial amount of hateful and abusive content as well. Therefore, it is important …","url":["https://arxiv.org/pdf/2203.13778"]}
+{"year":"2022","title":"L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi","authors":["A Joshi, A Kajale, J Gadre, S Deode, R Joshi - arXiv preprint arXiv:2211.11187, 2022"],"snippet":"Sentence representation from vanilla BERT models does not work well on sentence similarity tasks. Sentence-BERT models specifically trained on STS or NLI datasets are shown to provide state-of-the-art performance. However, building these models …","url":["https://arxiv.org/pdf/2211.11187"]}
+{"year":"2022","title":"Label Semantic Aware Pre-training for Few-shot Text Classification","authors":["A Mueller, J Krone, S Romeo, S Mansour, E Mansimov… - arXiv preprint arXiv …, 2022"],"snippet":"In text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification performance during fine-tuning and prediction. However, use of label-semantics …","url":["https://arxiv.org/pdf/2204.07128"]}
+{"year":"2022","title":"Landing AI on Networks: An equipment vendor viewpoint on Autonomous Driving Networks","authors":["D Rossi, L Zhang"],"snippet":"… Similarly, recently hyped advances [21] in NLP relied on hundred billions of text tokens corpus such as Common Crawl [47]. Even in lesser massmediatized fields such as computational biology, it is fairly well recognized that astonishing advances [48] …","url":["https://nonsns.github.io/paper/rossi22ai4net_vision.pdf"]}
+{"year":"2022","title":"Language Agnostic Code-Mixing Data Augmentation by Predicting Linguistic Patterns","authors":["SS Li, K Murray - arXiv preprint arXiv:2211.07628, 2022"],"snippet":"In this work, we focus on intrasentential code-mixing and propose several different Synthetic Code-Mixing (SCM) data augmentation methods that outperform the baseline on downstream sentiment analysis tasks across various amounts of …","url":["https://arxiv.org/pdf/2211.07628"]}
+{"year":"2022","title":"Language Agnostic Multilingual Information Retrieval with Contrastive Learning","authors":["X Hu, X Chen, P Qi, D Kong, K Liu, WY Wang, Z Huang - arXiv preprint arXiv …, 2022"],"snippet":"Multilingual information retrieval is challenging due to the lack of training datasets for many low-resource languages. We present an effective method by leveraging parallel and non-parallel corpora to improve the pretrained multilingual language …","url":["https://arxiv.org/pdf/2210.06633"]}
+{"year":"2022","title":"Language and Gender","authors":["J Berger, R Boghrati, S Rathee, R Pogacar, A Mecit - ACR North American Advances, 2021"],"snippet":"… We use Common Crawl and 11 million product reviews from Amazon and Yelp, to ask whether algorithms learn to associate women with … Common Crawl is a snapshot of the contents of the World Wide Web, a text repository of 2.45 billion web …","url":["https://www.acrwebsite.org/volumes/v49/acr_vol49_3000129.pdf"]}
+{"year":"2022","title":"Language Chameleon: Transformation analysis between languages using Cross-lingual Post-training based on Pre-trained language models","authors":["S Son, C Park, J Lee, M Shim, C Lee, Y Jang, J Seo… - arXiv preprint arXiv …, 2022"],"snippet":"… XLM-R XLM-R is a cross-lingual model (XLM), which is trained with commoncrawl corpus6 containing a hundred types of languages. Unlike previous XLM, it is based on RoBERTa. It has 550M … 6https://commoncrawl.org/ 7https://namu.wiki/ 8https://corpus.korean.go.kr/ …","url":["https://arxiv.org/pdf/2209.06422"]}
+{"year":"2022","title":"Language Detoxification with Attribute-Discriminative Latent Space","authors":["JM Kwak, M Kim, SJ Hwang - arXiv preprint arXiv:2210.10329, 2022"],"snippet":"Transformer-based Language Models (LMs) achieve remarkable performances on a variety of NLU tasks, but are also prone to generating toxic texts such as insults, threats, and profanities which limit their adaptations to the real-world applications …","url":["https://arxiv.org/pdf/2210.10329"]}
+{"year":"2022","title":"Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion","authors":["K Shuster, M Komeili, L Adolphs, S Roller, A Szlam… - arXiv preprint arXiv …, 2022"],"snippet":"… Knowledge Module Task To construct our knowledge task, we also start with Common Crawl, splitting it into sentences. We construct a Lucene5 search over Common Crawl, and then, for a given target sentence of a document, we find the …","url":["https://arxiv.org/pdf/2203.13224"]}
+{"year":"2022","title":"Language Pre-Training and Auxiliary Tasks for Vision and Language Navigation","authors":["S Bhatt - 2022"],"snippet":"The Vision and Language Navigation task came to life from the idea that we can build a robot or an autonomous system that can be instructed in human language and that will navigate using the instructions given. For example, we tell the agent to “Go …","url":["https://rc.library.uta.edu/uta-ir/bitstream/handle/10106/30243/BHATT-THESIS-2021.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Language-Agnostic Website Embedding and Classification","authors":["S Lugeon, T Piccardi, R West - arXiv preprint arXiv:2201.03677, 2022"],"snippet":"… Following this intuition, we collected from Common Crawl4, a large-scale sample of the Web, the 19 most frequent TLDs: .com, .org, .net, .info, … We consider the 30 most frequent metatags from a sample of the Common Crawl and represent their …","url":["https://arxiv.org/pdf/2201.03677"]}
+{"year":"2022","title":"Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation","authors":["Z Ding, T Hui, J Huang, X Wei, J Han, S Liu - … of the IEEE/CVF Conference on …, 2022"],"snippet":"… tic inputs, we adopt LSTM [9] to extract language features from GloVe word embeddings [32] pretrained on Common Crawl with 840B tokens. The maximum length of the input sentence is 25. We set the frame interval δ = 6 for calculating the …","url":["https://openaccess.thecvf.com/content/CVPR2022/papers/Ding_Language-Bridged_Spatial-Temporal_Interaction_for_Referring_Video_Object_Segmentation_CVPR_2022_paper.pdf"]}
+{"year":"2022","title":"Large Language Models Struggle to Learn Long-Tail Knowledge","authors":["N Kandpal, H Deng, A Roberts, E Wallace, C Raffel - arXiv preprint arXiv:2211.08411, 2022"],"snippet":"The internet contains a wealth of knowledge -- from the birthdays of historical figures to tutorials on how to code -- all of which may be learned by language models. However, there is a huge variability in the number of times a given piece of …","url":["https://arxiv.org/pdf/2211.08411"]}
+{"year":"2022","title":"Large pre-trained language models contain human-like biases of what is right and wrong to do","authors":["P Schramowski, C Turan, N Andersen, CA Rothkopf… - Nature Machine Intelligence, 2022"],"snippet":"Artificial writing is permeating our lives due to recent advances in large-scale, transformer-based language models (LMs) such as BERT, GPT-2 and GPT-3. Using them as pre-trained models and fine-tuning them for specific tasks, researchers have …","url":["https://www.nature.com/articles/s42256-022-00458-8"]}
+{"year":"2022","title":"Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All","authors":["E Guetta, A Shmidman, S Shmidman, CS Shmidman… - arXiv preprint arXiv …, 2022"],"snippet":"… Due to the lack of large public-domain textual corpora available for Modern Hebrew, we had to rely upon Wikipedia, Twitter, and the OSCAR common crawl Thus, other genres are unrepresented or underrepresented, including scientific …","url":["https://arxiv.org/pdf/2211.15199"]}
+{"year":"2022","title":"Large-scale Bilingual Language-Image Contrastive Learning","authors":["B Ko, G Gu - arXiv preprint arXiv:2203.14463, 2022"],"snippet":"This paper is a technical report to share our experience and findings building a Korean and English bilingual multimodal model. While many of the multimodal datasets focus on English and multilingual multimodal research uses machine-translated …","url":["https://arxiv.org/pdf/2203.14463"]}
+{"year":"2022","title":"Large-scale product classification for efficient matching in procurement systems","authors":["I Hrysha - 2022"],"snippet":"We consider the problem of recommending relevant suppliers given detailed request context in a procurement setting. The fundamental recommendation in procurement systems is that a single query has potentially hundreds of relevant …","url":["http://www.er.ucu.edu.ua:8080/bitstream/handle/1/3154/Hrysha%2C%20Ihor%20-%20Large-scale%20product%20classification%20for%20efficient%20matching%20in%20procurement%20systems.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Large-scale product classification to recommend suppliers in procurement systems","authors":["I Hrysha, S Grondahl"],"snippet":"We consider the problem of recommending relevant suppliers given detailed request context in a procurement setting. The fundamental recommendation in procurement systems is that a single query has potentially hundreds of relevant …","url":["https://s3.eu-central-1.amazonaws.com/ucu.edu.ua/wp-content/uploads/sites/8/2022/12/MS-AMLV_2022_paper_27.pdf"]}
+{"year":"2022","title":"Large-scale Semi-supervised Learning of Neural NLP Models","authors":["S Kiyono - 2022"],"snippet":"Deep neural network (DNN) based approaches have achieved remarkable performance in multiple research fields, such as natural language processing, computer vision, and speech processing. However, it is widely acknowledged that …","url":["https://www.cl.ecei.tohoku.ac.jp/publications/2022/kiyono-dthesis.pdf"]}
+{"year":"2022","title":"Large-scale study of web accessibility metrics","authors":["B Martins, C Duarte - Universal Access in the Information Society, 2022"],"snippet":"… The pages were obtained from CommonCrawl Footnote 5 . CommonCrawl is an open corpus of web crawl data, including metadata and source of billions of web pages since 2013. We used the most recent crawls to obtain the URLs of the pages …","url":["https://link.springer.com/article/10.1007/s10209-022-00956-x"]}
+{"year":"2022","title":"Laying the foundations for benchmarking open data automatically","authors":["AS Correa, FSC Da Silva"],"snippet":"… Common Crawl And Unlocking Web Archives For Research. Retrieved 2019-01-13 from https://www.forbes.com/sites/kalevleetaru/2017/09… Common Crawl And Unlocking Web Archives For Research. Retrieved 2019-01-13 from https://www.forbes.com/sites/kalevleetaru/2017/09…","url":["https://ouci.dntb.gov.ua/en/works/9j0eJBj4/"]}
+{"year":"2022","title":"Learner Profiling: Demographics Identification Based on NLP, Machine Learning, and MOOCs Metadata","authors":["T ALJOHANI, M MUSLIH - 2022"],"snippet":"Massive Open Online Courses (MOOCs) have become universal learning resources, and the COVID- 19 pandemic is rendering these platforms even more necessary. Many types of research are ongoing to improve the learning resources provided to …","url":["http://etheses.dur.ac.uk/14486/1/Thesis__Final_Version.pdf"]}
+{"year":"2022","title":"Learning GUI Completions with User-defined Constraints","authors":["L Brückner, LA Leiva, A Oulasvirta - ACM Transactions on Interactive Intelligent …, 2022","LA LEIVA - 2022"],"snippet":"A key objective in the design of graphical user interfaces (GUIs) is to ensure consistency across screens of the same product. However, designing a compliant layout is time-consuming and can distract designers from creative thinking. This …","url":["https://dl.acm.org/doi/abs/10.1145/3490034","https://research.aalto.fi/files/82497867/learning_gui_completions.pdf"]}
+{"year":"2022","title":"Learning High-Order Semantic Representation for Intent Classification and Slot Filling on Low-Resource Language via Hypergraph.","authors":["X Qi, Y Gao, R Wang, M Zhao, S Cui, M Mortazavi - Mathematical Problems in …, 2022"],"snippet":"… ey pretrained it on the Common Crawl and Wikipedia using fastText. is Indonesian word vector model is trained using CBOW with position-weights, in dimension 300 (ie, Wemb ∈ R1 × 300), with character n-grams of length 5, a window of size 5 and 10 …","url":["https://downloads.hindawi.com/journals/mpe/2022/8407713.pdf"]}
+{"year":"2022","title":"Learning interpretable word embeddings via bidirectional alignment of dimensions with semantic concepts","authors":["LK Şenel, F Şahinuç, V Yücesoy, H Schütze, T Çukur… - Information Processing & …, 2022"],"snippet":"We propose bidirectional imparting or BiImp, a generalized method for aligning embedding dimensions with concepts during the embedding learning phase. While preserving the semantic structure of the embedding space, BiImp makes dimensions …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322000498"]}
+{"year":"2022","title":"Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings","authors":["D Bollegala - arXiv preprint arXiv:2204.12386, 2022"],"snippet":"… Note that this is significantly smaller compared to vocabulary sizes and training corpora used in publicly available word embeddings (eg GloVe embeddings are trained on 42B tokens from Common Crawl corpus covering …","url":["https://arxiv.org/pdf/2204.12386"]}
+{"year":"2022","title":"Learning on Streaming Graphs with Experience Replay","authors":["M Perini, G Ramponi, P Carbone, V Kalavri - 2022"],"snippet":"… Text features have been generated using a 300-dimensional GloVe CommonCrawl word vector. Posts are linked with an edge if they have been commented by the same user and each edge bears the timestamp of the first comment. The …","url":["https://sites.bu.edu/casp/files/2021/12/online-gnn-SAC-preprint.pdf"]}
+{"year":"2022","title":"Learning Sample Importance for Cross-Scenario Video Temporal Grounding","authors":["P Bao, Y Mu - arXiv preprint arXiv:2201.02848, 2022"],"snippet":"The task of temporal grounding aims to locate video moment in an untrimmed video, with a given sentence query. This paper for the first time investigates some superficial biases that are specific to the temporal grounding task, and proposes a …","url":["https://arxiv.org/pdf/2201.02848"]}
+{"year":"2022","title":"Learning the Morphological and Syntactic Grammars for Named Entity Recognition","authors":["M Sun, Q Yang, H Wang, M Pasquine, IA Hameed - Information, 2022"],"snippet":"In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structures, such as inflection, that will confuse the data-driven models when perceiving the word’s actual meaning. This work tries to alleviate …","url":["https://www.mdpi.com/2078-2489/13/2/49/pdf"]}
+{"year":"2022","title":"Learning the Morphological and Syntactic Grammars for Named Entity Recognition. Information 2022, 13, 49","authors":["M Sun, Q Yang, H Wang, M Pasquine, IA Hameed - 2022"],"snippet":"In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structures, such as inflection, that will confuse the data-driven models when perceiving the word’s actual meaning. This work tries to alleviate …","url":["https://www.researchgate.net/profile/Ibrahim-Hameed/publication/357970212_Learning_the_Morphological_and_Syntactic_Grammars_for_Named_Entity_Recognition/links/61e97f849a753545e2e50b09/Learning-the-Morphological-and-Syntactic-Grammars-for-Named-Entity-Recognition.pdf"]}
+{"year":"2022","title":"Learning to Enrich Query Representation with Pseudo-Relevance Feedback for Cross-lingual Retrieval","authors":["R Chandradevan, E Yang, M Yarmohammadi… - Proceedings of the 45th …, 2022"],"snippet":"… To help picking the best performing model across the training steps and tune the free parameters, we used CLIR Common Crawl Collection (HC4) [13] as the development dataset. In this dataset, the exact same English topics are queried over …","url":["https://dl.acm.org/doi/abs/10.1145/3477495.3532013"]}
+{"year":"2022","title":"Learning to Follow Instructions in Text-Based Games","authors":["M Tuli, AC Li, P Vaezipoor, TQ Klassen, S Sanner… - arXiv preprint arXiv …, 2022"],"snippet":"Text-based games present a unique class of sequential decision making problem in which agents interact with a partially observable, simulated environment via actions and observations conveyed through natural language. Such observations typically …","url":["https://arxiv.org/pdf/2211.04591"]}
+{"year":"2022","title":"Learning to translate by learning to communicate","authors":["CM Downey, LZ Liu, X Zhou, S Steinert-Threlkeld - arXiv preprint arXiv:2207.07025, 2022"],"snippet":"We formulate and test a technique to use Emergent Communication (EC) with a pretrained multilingual model to improve on modern Unsupervised NMT systems, especially for low-resource languages. It has been argued that the currently …","url":["https://arxiv.org/pdf/2207.07025"]}
+{"year":"2022","title":"Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search","authors":["D Zhang, A Vakili Tahami, M Abualsaud, M Smucker - 2022"],"snippet":"When searching the web for answers to health questions, people can make incorrect decisions that have a negative effect on their lives if the search results contain misinformation. To reduce health misinformation in search results, we need to be …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18257/SIGIR%202022%20Misinformation.pdf?sequence=1"]}
+{"year":"2022","title":"Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning","authors":["T Mu, K Lin, F Niu, G Thattai - arXiv preprint arXiv:2201.08520, 2022"],"snippet":"We present a two-step hybrid reinforcement learning (RL) policy that is designed to generate interpretable and robust hierarchical policies on the RL problem with graph-based input. Unlike prior deep reinforcement learning policies parameterized by an end-to-end …","url":["https://arxiv.org/pdf/2201.08520"]}
+{"year":"2022","title":"Learnings from Federated Learning in the Real world","authors":["C Dupuy, TG Roosta, L Long, C Chung, R Gupta… - arXiv preprint arXiv …, 2022"],"snippet":"Federated Learning (FL) applied to real world data may suffer from several idiosyncrasies. One such idiosyncrasy is the data distribution across devices. Data across devices could be distributed such that there are some \"heavy devices\" with …","url":["https://arxiv.org/pdf/2202.03925"]}
+{"year":"2022","title":"Less is More: Task-aware Layer-wise Distillation for Language Model Compression","authors":["C Liang, S Zuo, Q Zhang, P He, W Chen, T Zhao - arXiv preprint arXiv:2210.01351, 2022"],"snippet":"Layer-wise distillation is a powerful tool to compress large models (ie teacher models) into small ones (ie, student models). The student distills knowledge from the teacher by mimicking the hidden representations of the teacher at every intermediate layer …","url":["https://web7.arxiv.org/pdf/2210.01351"]}
+{"year":"2022","title":"Lessons learned from the evaluation of Spanish Language Models","authors":["R Agerri Gascón, E Agirre Bengoa - 2023","R Agerri, E Agirre - arXiv preprint arXiv:2212.08390, 2022"],"snippet":"Given the impact of language models on the field of Natural Language Processing, a number of Spanish encoder-only masked language models (aka BERTs) have been trained and released. These models were developed either within large projects …","url":["https://arxiv.org/pdf/2212.08390","https://rua.ua.es/dspace/bitstream/10045/133264/1/PLN_70_13.pdf"]}
+{"year":"2022","title":"Leveraging Natural Supervision for Language Representation Learning and Generation","authors":["M Chen - arXiv preprint arXiv:2207.10617, 2022"],"snippet":"Recent breakthroughs in Natural Language Processing (NLP) have been driven by language models trained on a massive amount of plain text. While powerful, deriving supervision from textual resources is still an open question. For example, language …","url":["https://arxiv.org/pdf/2207.10617"]}
+{"year":"2022","title":"LeviRANK: Limited Query Expansion with Voting Integration for Document Retrieval and Ranking","authors":["A Rana, P Golchha, R Juntunen, A Coajă… - Working Notes Papers of the …, 2022"],"snippet":"In order to make informed decisions in personal life, the information available on the internet is often overwhelming, and thus comparative decision-making is particularly challenging. Given the plethora of online resources, it often results in wastage of …","url":["http://ceur-ws.org/Vol-3180/paper-259.pdf"]}
+{"year":"2022","title":"Lexical Semantics with Large Language Models: A Case Study of English break","authors":["E Petersen, C Potts"],"snippet":"Large neural language models (LLMs) can be powerful tools for research in lexical semantics. We illustrate this potential using the English verb break, which has numerous senses and appears in a wide range of syntactic frames. We show that …","url":["https://lingbuzz.net/lingbuzz/006859/current.pdf"]}
+{"year":"2022","title":"Lightweight diacritics restoration for V4 languages","authors":["B Csanády, A Lukács"],"snippet":"… In the case of HunWeb2, we used the \"2017-2018\" part of the Common Crawl subcorpus. Not splitting up the documents ensures that the train and dev data do not correlate too much, as we have found that there can be a lot of repeated sentences …","url":["http://acta.bibl.u-szeged.hu/75899/1/msznykonf_018_549-559.pdf"]}
+{"year":"2022","title":"Limitations and Challenges of Unsupervised Cross-lingual Pre-training","authors":["MQ Zaragoza, F Casacuberta - Proceedings of the 15th biennial conference of the …, 2022"],"snippet":"Cross-lingual alignment methods for monolingual language representations have received notable attention in recent years. However, their use in machine translation pre-training remains scarce. This work tries to shed light on the effects of some of the …","url":["https://aclanthology.org/2022.amta-research.13.pdf"]}
+{"year":"2022","title":"Linguistic and Emotion-based Identification of Tweets with Fake News: A Case Study","authors":["VS Bernardes - 2021"],"snippet":"Since the popularization of the term in 2016, we have observed a proliferation of so called “fake news” content, assisted by the widespread use of social media platforms. The dissemination of fake content brings with it serious political, economical, and …","url":["https://repositorio-aberto.up.pt/bitstream/10216/139434/2/528149.pdf"]}
+{"year":"2022","title":"Linguistic Approaches to the Analysis of Online Terrorist Threats","authors":["J Longhi - Language as Evidence, 2022"],"snippet":"This chapter focuses on online terrorist threats. For many linguists, the best training for a forensic linguist is a course in descriptive and applied linguistics because each case will normally require a different selection of tools from the linguistic toolbox …","url":["https://link.springer.com/chapter/10.1007/978-3-030-84330-4_13"]}
+{"year":"2022","title":"Linguistic resources for Romanian. Quality assessed machine-translated and post-edited Romanian corpus and opportunities for interdisciplinary research","authors":["G BULGARU - REVUE INTERNATIONALE D'ÉTUDES EN LANGUES …"],"snippet":"Despite the great progress over the last years, Romanian is still a low-resourced language. In this paper, we set to make a short overview of the language technology field and the linguistic resources available for Romanian. We also sketch out a short …","url":["https://www.academia.edu/download/77452310/RIELMA_no14_2021_Supplement.pdf#page=78"]}
+{"year":"2022","title":"LinkingPark: An automatic semantic table interpretation system","authors":["S Chen, A Karaoglu, C Negreanu, T Ma, JG Yao… - Journal of Web Semantics, 2022"],"snippet":"In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation …","url":["https://www.sciencedirect.com/science/article/pii/S1570826822000233"]}
+{"year":"2022","title":"liveopp/keras-quora-question-pairs","authors":["GPK Tool, JFMAM Jun, JASON Dec, JSMTW Thu, F Sat"],"snippet":"… Max bag-of-embeddings (this work) GloVe Common Crawl (840B tokens, 300D) 0.83 \"Multi-Perspective-LSTM\" [5] GloVe Common Crawl (840B tokens, 300D) 0.83 … \"Max-out Window Encoding\" with depth 2 [7] GloVe Common Crawl pruned to 1M …","url":["https://giters.com/liveopp/keras-quora-question-pairs"]}
+{"year":"2022","title":"LLM. int8 (): 8-bit Matrix Multiplication for Transformers at Scale","authors":["T Dettmers, M Lewis, Y Belkada, L Zettlemoyer - arXiv preprint arXiv:2208.07339, 2022"],"snippet":"Large language models have been widely adopted but require significant GPU memory for inference. We develop a procedure for Int8 matrix multiplication for feed-forward and attention projection layers in transformers, which cut the memory needed for …","url":["https://arxiv.org/pdf/2208.07339"]}
+{"year":"2022","title":"lo-fi: distributed fine-tuning without communication","authors":["M Wortsman, S Gururangan, S Li, A Farhadi, L Schmidt… - arXiv preprint arXiv …, 2022"],"snippet":"… -tuning OPT language models (up to 1.3B parameters) on Common Crawl. By removing the communication requirement, lo-fi reduces resource … Finally, we test lo-fi beyond computer vision by fine-tuning OPT-125M and OPT-1.3B [72] on …","url":["https://arxiv.org/pdf/2210.11948"]}
+{"year":"2022","title":"Location-based Twitter Filtering for the Creation of Low-Resource Language Datasets in Indonesian Local Languages","authors":["M Amien, C Feng, H Huang - arXiv preprint arXiv:2206.07238, 2022"],"snippet":"Twitter contains an abundance of linguistic data from the real world. We examine Twitter for user-generated content in low-resource languages such as local Indonesian. For NLP to work in Indonesian, it must consider local dialects …","url":["https://arxiv.org/pdf/2206.07238"]}
+{"year":"2022","title":"Longitudinal analysis of sentiment and emotion in news media headlines using automated labelling with Transformer language models","authors":["D Rozado, R Hughes, J Halberstadt - Plos one, 2022"],"snippet":"This work describes a chronological (2000–2019) analysis of sentiment and emotion in 23 million headlines from 47 news media outlets popular in the United States. We use Transformer language models fine-tuned for detection of sentiment (positive …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0276367"]}
+{"year":"2022","title":"Low-level factors increase gaze-guidance under cognitive load: A comparison of image-salience and semantic-salience models","authors":["K Walter, P Bex - PLOS ONE, 2022"],"snippet":"… GloVe is trained on large web-based datasets, we used the Common Crawl dataset comprised of 840 billion tokens and 2.2 million words. GloVe categorizes words along feature dimensions to create a similarity web of various terms based on …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277691"]}
+{"year":"2022","title":"Low-Resource Authorship Style Transfer with In-Context Learning","authors":["A Patel, N Andrews, C Callison-Burch - arXiv preprint arXiv:2212.08986, 2022"],"snippet":"… Other models were trained on variants of Common Crawl data. To the best of our knowledge, using various search … Common Crawl, as a breadth-first crawler, only contains a small amount of Reddit data, often a few thousand pages per month …","url":["https://arxiv.org/pdf/2212.08986"]}
+{"year":"2022","title":"LPT: Language-agnostic Prompt Tuning","authors":["Y Ji, Y Wang, Z Tang - Sci China Inf Sci"],"snippet":"… The pre-trained XLM-RoBERTa-base model contains 270M parameters, which is trained on 2.5 TB CommonCrawl data in 100 languages. Its vocabulary contains 250k tokens. The architecture of XLMRoBERTa-base is the same as RoBERTa-base. …","url":["https://lijuntaopku.github.io/SCIS_22_LPT.pdf"]}
+{"year":"2022","title":"Machine Comprehension System in Tamil and English based on BERT","authors":["G Srivatsun, S Thivaharan, BK KS, S Sudharsan - 2022 3rd International Conference …, 2022"],"snippet":"… XLM-R [6] used more than 2 terabytes of data filtered by Common Crawl to train a Transformer-based masked language model on 100 languages. It also gave a complete empirical study of the essential aspects that are necessary to improve cross-lingual …","url":["https://ieeexplore.ieee.org/abstract/document/9885657/"]}
+{"year":"2022","title":"Machine Learning and Deep Learning Based Phishing Websites Detection: The Current Gaps and Next Directions","authors":["K Adane, B Beyene - Review of Computer Engineering Research, 2022"],"snippet":"There are many phishing websites detection techniques in literature, namely white-listing, black-listing, visual-similarity, heuristic-based, and others. However, detecting zero-hour or newly designed phishing website attacks is an inherent property of machine …","url":["https://archive.conscientiabeam.com/index.php/76/article/download/2983/6434"]}
+{"year":"2022","title":"Machine learning and deep learning-based Natural Language Processing for auto-vetting the appropriateness of Lumbar Spine Magnetic Resonance Imaging …","authors":["A Alanazi, A Cradock, J Ryan, L Rainford - Informatics in Medicine Unlocked, 2022"],"snippet":"Manual vetting of radiology referrals is an essential daily task to ensure the appropriateness of the received referrals. Such tasks require sufficient clinical experience and may challenge the radiology staff. With the emerging of artificial …","url":["https://www.sciencedirect.com/science/article/pii/S2352914822001071"]}
+{"year":"2022","title":"Machine Learning approaches for Topic and Sentiment Analysis in multilingual opinions and low-resource languages: From English to Guarani","authors":["MM Agüero Torales - 2022"],"snippet":"This dissertation has focused on the study of machine learning techniques for sentiment analysis and topic modeling in texts from social media. It puts a special emphasis on approaches and methods for handling low-resource languages, ie …","url":["https://digibug.ugr.es/bitstream/handle/10481/72863/80733.pdf?sequence=4&isAllowed=y"]}
+{"year":"2022","title":"Machine Reading at Scale: A Search Engine for Scientific and Academic Research","authors":["N Sousa, N Oliveira, I Praça - Systems, 2022"],"snippet":"The Internet, much like our universe, is ever-expanding. Information, in the most varied formats, is continuously added to the point of information overload. Consequently, the ability to navigate this ocean of data is crucial in our day-to-day …","url":["https://www.mdpi.com/2079-8954/10/2/43/pdf"]}
+{"year":"2022","title":"Machine Reading at Scale: A Search Engine for Scientific and Academic Research. Systems 2022, 10, 43","authors":["N Sousa, N Oliveira, I Praça - 2022"],"snippet":"The Internet, much like our universe, is ever-expanding. Information, in the most varied formats, is continuously added to the point of information overload. Consequently, the ability to navigate this ocean of data is crucial in our day-to-day …","url":["https://www.mdpi.com/2079-8954/10/2/43/pdf?version=1649908028"]}
+{"year":"2022","title":"Machine Translation Performance Prediction System: Optimal Prediction for Optimal Translation","authors":["E Biçici - SN Computer Science, 2022"],"snippet":"Abstract Machine translation performance prediction (MTPP) system (MTPPS) is an automatic, accurate, language and natural language processing (NLP) output independent prediction model. MTPPS is optimal by the capability to predict …","url":["https://link.springer.com/article/10.1007/s42979-022-01183-0"]}
+{"year":"2022","title":"Machine's Conceptual Development Using FNet","authors":["D Jayanna - 2022"],"snippet":"Masked language modeling (MLM) is a well-known technique in Natural languageprocessing (NLP) to train a model on randomly masked tokens and use the trainedmodel to predict the masked words. FNet is a recently developed Fourier …","url":["https://search.proquest.com/openview/8e85ce3a1dea6ec809b32142fbb3db6c/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Making AI work for skills-based training: A case study","authors":["R Robson, E Kelsey, A Goel, L Egerton, S Nasir…"],"snippet":"Motivated by the need to upskill workers rapidly and equitably in response to changes in work and the workplace, a team funded by the US National Science Foundation Convergence Accelerator program has developed and piloted an …","url":["https://www.researchgate.net/profile/Robby-Robson/publication/361742207_Extended_Abstract_Making_AI_work_for_skills-based_training_A_case_study/links/62c2fbd0c692f45113050e62/Extended-Abstract-Making-AI-work-for-skills-based-training-A-case-study.pdf"]}
+{"year":"2022","title":"MalGen: Malware Generation with Specific Behaviors to Improve Machine Learning-based Detectors.","authors":["M Smith, A Carbajal, E Domschot, NT Johnson… - 2022"],"snippet":"In recent years, infections and damage caused by malware have increased at exponential rates. At the same time, machine learning (ML) techniques have shown tremendous promise in many domains, often out performing human efforts by …","url":["https://www.osti.gov/servlets/purl/1893244"]}
+{"year":"2022","title":"MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages","authors":["S Sonkar, Z Wang, RG Baraniuk - arXiv preprint arXiv:2212.09723, 2022"],"snippet":"This paper investigates the problem of Named Entity Recognition (NER) for extreme low-resource languages with only a few hundred tagged data samples. NER is a fundamental task in Natural Language Processing (NLP). A critical driver …","url":["https://arxiv.org/pdf/2212.09723"]}
+{"year":"2022","title":"Manifold's English-Chinese System at WMT22 General MT Task","authors":["C Jin, T Shi, Z Xue, X Lin - Proceedings of the Seventh Conference on Machine …, 2022"],"snippet":"Manifold’s English-Chinese System at WMT22 is an ensemble of 4 models trained by different configurations with scheduled sampling-based fine-tuning. The four configurations are DeepBig (XenC), DeepLarger (XenC), DeepBig-TalkingHeads (XenC) …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.20.pdf"]}
+{"year":"2022","title":"Many Languages, One Deep Learning Model Multilingual understanding is easier than you think!","authors":["C Wolfe"],"snippet":"How do we enable natural language-based deep learning systems to understand data in many languages? One naive approach would be to simply train a separate deep learning model on each of the desired languages. But, this approach is pretty …","url":["https://towardsdatascience.com/many-languages-one-deep-learning-model-69201d02dee1"]}
+{"year":"2022","title":"Marathi Social Media Opinion Mining using XLM-R","authors":["N Rathod, N Mistry, D Talati, M Parikh, A Kore… - … International Conference on …, 2022"],"snippet":"… XLM-R is a transformer-based multilingual masked model pre-trained on CommonCrawl data in 100 languages with base having 250M parameters, which obtains state-of-the-art results in the tasks of question answering, sequence labeling …","url":["https://ieeexplore.ieee.org/abstract/document/9793308/"]}
+{"year":"2022","title":"Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability","authors":["Y Fujinuma, J Boyd-Graber, K Kann - arXiv preprint arXiv:2203.10753, 2022"],"snippet":"Pretrained multilingual models enable zero-shot learning even for unseen languages, and that performance can be further improved via adaptation prior to finetuning. However, it is unclear how the number of pretraining languages …","url":["https://arxiv.org/pdf/2203.10753"]}
+{"year":"2022","title":"Matching Tweets With Applicable Fact-Checks Across Languages","authors":["A Kazemi, Z Li, V Pérez-Rosas, SA Hale, R Mihalcea - arXiv preprint arXiv …, 2022"],"snippet":"… The model is trained on more than 2TBs CommonCrawl data and supports one hundred languages. We also rely on recent language … language modeling trained on 17 billion monolingual sentences from CommonCrawl and 6 billion translated …","url":["https://arxiv.org/pdf/2202.07094"]}
+{"year":"2022","title":"Measuring document similarity with weighted averages of word embeddings.","authors":["B Seegmiller, D Papanikolaou, LDW Schmidt - Explorations in Economic History, 2022"],"snippet":"We detail a methodology for estimating the textual similarity between two documents while accounting for the possibility that two different words can have a similar meaning. We illustrate the method’s usefulness in facilitating comparisons between …","url":["https://www.sciencedirect.com/science/article/pii/S0014498322000729"]}
+{"year":"2022","title":"Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender Signals","authors":["SO Sabbaghi, A Caliskan - arXiv preprint arXiv:2206.01691, 2022"],"snippet":"Does the grammatical gender of a language interfere when measuring the semantic gender information captured by its word embeddings? A number of anomalous gender bias measurements in the embeddings of gendered languages suggest this …","url":["https://arxiv.org/pdf/2206.01691"]}
+{"year":"2022","title":"Measuring harmful and toxic representations in Scandinavian language models","authors":["S Touileb"],"snippet":"… Combination of Danish texts from Common Crawl, Wikipedia, debate forums, and OpenSubtitles. DanishRoBERTa Danish subset of mC4 (from the Common Crawl). …","url":["https://mediafutures.no/wp-content/uploads/WP-5-1-ST_MF_annual_meeting_2022-min.pdf"]}
+{"year":"2022","title":"Measuring Harmful Representations in Scandinavian Language Models","authors":["S Touileb, D Nozza - arXiv preprint arXiv:2211.11678, 2022"],"snippet":"… trained on subsets of the Common Crawl corpus. The remaining four models were trained on datasets comprising languagespecific subsets from the Common Crawl. As previous works have shown that this corpus contains various types of …","url":["https://arxiv.org/pdf/2211.11678"]}
+{"year":"2022","title":"MEASURING NETWORK INTERFERENCE AND MITIGATING IT WITH DNS ENCRYPTION","authors":["SA Akhavan Niaki - 2022"],"snippet":"The Internet has emerged as one of the most important tools of communication. With around 4.5 billion active users as of July 2020, it provides people the opportunity to access a vast treasure trove of information and express their opinions online. How-ever …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=3583&context=dissertations_2"]}
+{"year":"2022","title":"Measuring Similarity by Linguistic Features rather than Frequency","authors":["R Delmonte, N Busetto"],"snippet":"… As said above, we used BERT – with the Italian model taken from UWAC corpus, Umbertocommoncrawl - and examined the output of the first or projection layer5. In this way we intended to check the predicting ability of BERT on the masked word, by …","url":["https://sigsem.uvt.nl/isa18/ISA-18_11_Paper.pdf"]}
+{"year":"2022","title":"Measuring the Impact of (Psycho-) Linguistic and Readability Features and Their Spill Over Effects on the Prediction of Eye Movement Patterns","authors":["D Wiechmann, Y Qiao, E Kerz, J Mattern - arXiv preprint arXiv:2203.08085, 2022"],"snippet":"… BERT is trained on the BooksCorpus (800M words) and Wikipedia (2,500M words), whereas GPT-2 is trained on WebText, an 8-million documents subset of CommonCrawl amounting to 40 GB of text. We chose the BERT base model (cased) …","url":["https://arxiv.org/pdf/2203.08085"]}
+{"year":"2022","title":"Memory in humans and deep language models: Linking hypotheses for model augmentation","authors":["O Raccah, P Chen, TL Willke, D Poeppel, VA Vo - arXiv preprint arXiv:2210.01869, 2022"],"snippet":"The computational complexity of the self-attention mechanism in Transformer models significantly limits their ability to generalize over long temporal durations. Memory-augmentation, or the explicit storing of past information in external memory …","url":["https://web7.arxiv.org/pdf/2210.01869"]}
+{"year":"2022","title":"Mental Health Disorder Identification From Motivational Conversations","authors":["T Saha, SM Reddy, S Saha, P Bhattacharyya - IEEE Transactions on Computational …, 2022"],"snippet":"… 1) Embedding Features: To extract textual features of an utterance U having nu number of words, the representation of each of the words, w1,...,wu, where wi ∈ Rdu , wi s are obtained from the GloVe embeddings trained on the Common Crawl …","url":["https://ieeexplore.ieee.org/abstract/document/9729467/"]}
+{"year":"2022","title":"Menu close","authors":["J Ogden, M Kurzmeier, F Clavert, M Currie - 2022"],"snippet":"The aim of this guide is to provide a starting point for using web archives as a source for social science research. This guide provides a primer for how to approach web archives research design by first outlining what web archives are and how they differ …","url":["https://methods.sagepub.com/how-to-guide/how-to-design-web-archives-research"]}
+{"year":"2022","title":"Meta-Learning for Offensive Language Detection in Code-Mixed Texts","authors":["G Vadakkekara Suresh, BR Chakravarthi, JP McCrae - Forum for Information …, 2021"],"snippet":"This research investigates the application of Model-Agnostic Meta-Learning (MAML) and ProtoMAML to identify offensive code-mixed text content on social media in Tamil-English and Malayalam-English code-mixed texts. We follow a two-step …","url":["https://dl.acm.org/doi/pdf/10.1145/3503162.3503167"]}
+{"year":"2022","title":"METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals","authors":["P Bajaj, C Xiong, G Ke, X Liu, D He, S Tiwary, TY Liu… - arXiv preprint arXiv …, 2022"],"snippet":"We present an efficient method of pretraining large-scale autoencoding language models using training signals generated by an auxiliary model. Originated in ELECTRA, this training strategy has demonstrated sample-efficiency to pretrain …","url":["https://arxiv.org/pdf/2204.06644"]}
+{"year":"2022","title":"mFACE: Multilingual Summarization with Factual Consistency Evaluation","authors":["R Aharoni, S Narayan, J Maynez, J Herzig, E Clark… - arXiv preprint arXiv …, 2022"],"snippet":"Abstractive summarization has enjoyed renewed interest in recent years, thanks to pre-trained language models and the availability of large-scale datasets. Despite promising results, current models still suffer from generating factually inconsistent …","url":["https://arxiv.org/pdf/2212.10622"]}
+{"year":"2022","title":"mGPT: Few-Shot Learners Go Multilingual","authors":["O Shliazhko, A Fenogenova, M Tikhonova, V Mikhailov… - arXiv preprint arXiv …, 2022"],"snippet":"Recent studies report that autoregressive language models can successfully solve many NLP tasks via zeroand few-shot learning paradigms, which opens up new possibilities for using the pre-trained language models. This paper introduces two …","url":["https://arxiv.org/pdf/2204.07580"]}
+{"year":"2022","title":"MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge","authors":["L Fan, G Wang, Y Jiang, A Mandlekar, Y Yang, H Zhu… - arXiv preprint arXiv …, 2022"],"snippet":"Autonomous agents have made great strides in specialist domains like Atari games and Go. However, they typically learn tabula rasa in isolated environments with limited and manually conceived objectives, thus failing to generalize across a wide …","url":["https://arxiv.org/pdf/2206.08853"]}
+{"year":"2022","title":"Mini-Model Adaptation: Efficiently Extending Pretrained Models to New Languages via Aligned Shallow Training","authors":["K Marchisio, P Lewis, Y Chen, M Artetxe - arXiv preprint arXiv:2212.10503, 2022"],"snippet":"… 2020) as our training corpus, which is a filtered version of CommonCrawl. We report the full list of languages along with their corpus size and linguistic details in Table 1. Each language is preprocessed individually using SentencePiece (Kudo …","url":["https://arxiv.org/pdf/2212.10503"]}
+{"year":"2022","title":"minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models","authors":["K Misra - arXiv preprint arXiv:2203.13112, 2022"],"snippet":"We present minicons, an open source library that provides a standard API for researchers interested in conducting behavioral and representational analyses of transformer-based language models (LMs). Specifically, minicons enables …","url":["https://arxiv.org/pdf/2203.13112"]}
+{"year":"2022","title":"Misreporting and Fake News Detection Techniques on the Social Media Platform","authors":["Y Feng - Highlights in Science, Engineering and Technology, 2022"],"snippet":"… RealNews is also a news article dataset scraped from Common Crawl with newspaper python library. The training sample includes the news dump from Common Crawl ranging from December 2016 to March 2019, and the articles in …","url":["https://drpress.org/ojs/index.php/HSET/article/download/1417/1344"]}
+{"year":"2022","title":"Misspelling Semantics in Thai","authors":["P Nakwijit, M Purver"],"snippet":"User-generated content is full of misspellings. Rather than being just random noise, we hypothesise that many misspellings contain hidden semantics that can be leveraged for language understanding tasks. This paper presents a fine-grained …","url":["http://www.eecs.qmul.ac.uk/~mpurver/papers/nakwijit-purver22lrec.pdf"]}
+{"year":"2022","title":"MLGL-MP: a Multi-Label Graph Learning framework enhanced by pathway interdependence for Metabolic Pathway prediction","authors":["BX Du, PC Zhao, B Zhu, SM Yiu, AK Nyamabo, H Yu… - Bioinformatics, 2022"],"snippet":"Motivation During lead compound optimization, it is crucial to identify pathways where a drug-like compound is metabolized. Recently, machine learning-based methods have achieved inspiring progress to predict potential metabolic pathways …","url":["https://academic.oup.com/bioinformatics/article/38/Supplement_1/i325/6617514"]}
+{"year":"2022","title":"Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings","authors":["I García-Ferrero, R Agerri, G Rigau - arXiv preprint arXiv:2210.12623, 2022"],"snippet":"Zero-resource cross-lingual transfer approaches aim to apply supervised models from a source language to unlabelled target languages. In this paper we perform an in-depth study of the two main techniques employed so far for cross-lingual zero-resource …","url":["https://arxiv.org/pdf/2210.12623"]}
+{"year":"2022","title":"Modeling Associative Reasoning Processes","authors":["U Furbach, C Schon, M Ragni - arXiv preprint arXiv:2201.00716, 2022"],"snippet":"The human capability to reason about one domain by using knowledge of other domains has been researched for more than 50 years, but models that are formally sound and predict cognitive process are sparse. We propose a formally sound …","url":["https://arxiv.org/pdf/2201.00716"]}
+{"year":"2022","title":"Modeling Intensification for Sign Language Generation: A Computational Approach","authors":["M İnan, Y Zhong, S Hassan, L Quandt, M Alikhani - arXiv preprint arXiv:2203.09679, 2022"],"snippet":"End-to-end sign language generation models do not accurately represent the prosody in sign language. A lack of temporal and spatial variations leads to poor-quality generated presentations that confuse human interpreters. In this paper, we aim to …","url":["https://arxiv.org/pdf/2203.09679"]}
+{"year":"2022","title":"Modeling Target-Side Morphology in Neural Machine Translation: A Comparison of Strategies","authors":["MWD Marco, M Huck, A Fraser - arXiv preprint arXiv:2203.13550, 2022"],"snippet":"Morphologically rich languages pose difficulties to machine translation. Machine translation engines that rely on statistical learning from parallel training data, such as state-of-the-art neural systems, face challenges especially with rich morphology …","url":["https://arxiv.org/pdf/2203.13550"]}
+{"year":"2022","title":"Modelling Commonsense Properties using Pre-Trained Bi-Encoders","authors":["A Gajbhiye, L Espinosa-Anke, S Schockaert - arXiv preprint arXiv:2210.02771, 2022"],"snippet":"Grasping the commonsense properties of everyday concepts is an important prerequisite to language understanding. While contextualised language models are reportedly capable of predicting such commonsense properties with human-level …","url":["https://arxiv.org/pdf/2210.02771"]}
+{"year":"2022","title":"MODERN INFORMATION TECHNOLOGIES AND IT-EDUCATION","authors":["AM NEGANOV - MODERN INFORMATION, 2022"],"snippet":"… The experiments in this section are performed with a CommonCrawl data . The CommonCrawl is an open repository of web crawl data. Said … The vocabulary of the CommonCrawl text is plenty rich due to nearly all human languages present in …","url":["https://elibrary.ru/item.asp?id=49299792"]}
+{"year":"2022","title":"MOE/RF: A Novel Phishing Detection Model based on Revised Multi-Objective Evolution Optimization Algorithm and Random Forest","authors":["E Zhu, Z Chen, J Cui, H Zhong - IEEE Transactions on Network and Service …, 2022"],"snippet":"To effectively boost computer usage, machine learning models are used in several phishing detection systems to classify enormous phishing datasets. Based on phishing patterns, researchers prefer to extract a considerable number of features to …","url":["https://ieeexplore.ieee.org/abstract/document/9744099/"]}
+{"year":"2022","title":"Mokey: Enabling Narrow Fixed-Point Inference for Out-of-the-Box Floating-Point Transformer Models","authors":["AH Zadeh, M Mahmoud, A Abdelhadi, A Moshovos - arXiv preprint arXiv:2203.12758, 2022"],"snippet":"Increasingly larger and better Transformer models keep advancing state-of-the-art accuracy and capability for Natural Language Processing applications. These models demand more computational power, storage, and energy. Mokey reduces …","url":["https://arxiv.org/pdf/2203.12758"]}
+{"year":"2022","title":"Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi","authors":["A Velankar, H Patil, R Joshi - arXiv preprint arXiv:2204.08669, 2022"],"snippet":"Transformers are the most eminent architectures used for a vast range of Natural Language Processing tasks. These models are pre-trained over a large text corpus and are meant to serve state-of-the-art results over tasks like text classification. In …","url":["https://arxiv.org/pdf/2204.08669"]}
+{"year":"2022","title":"MonoByte: A Pool of Monolingual Byte-level Language Models","authors":["H Abonizio, LR de Souza, R Lotufo, R Nogueira - arXiv preprint arXiv:2209.11035, 2022"],"snippet":"… 2021b), the same corpus used to train mT5 and ByT5, which comprises 101 natural languages extracted from the Common Crawl web scrape. For each model, we selected only the documents written in the specific language, which was originally …","url":["https://arxiv.org/pdf/2209.11035"]}
+{"year":"2022","title":"Moving Stuff Around","authors":["A Câmara, C Hauff - 2022"],"snippet":"When training neural rankers with Large Language models, a practitioner generally leverages multiple GPUs, which increases the amount of available VRAM, allowing larger batches, and decreasing training time. However, managing how data moves …","url":["https://reneuir.org/assets/pdfs/ReNeuIR_2022_paper_2376.pdf"]}
+{"year":"2022","title":"MSCTD: A Multimodal Sentiment Chat Translation Dataset","authors":["Y Liang, F Meng, J Xu, Y Chen, J Zhou - arXiv preprint arXiv:2202.13645, 2022"],"snippet":"Multimodal machine translation and textual chat translation have received considerable attention in recent years. Although the conversation in its natural form is usually multimodal, there still lacks work on multimodal machine translation in …","url":["https://arxiv.org/pdf/2202.13645"]}
+{"year":"2022","title":"mSLAM: Massively multilingual joint pre-training for speech and text","authors":["A Bapna, C Cherry, Y Zhang, Y Jia, M Johnson… - arXiv preprint arXiv …, 2022"],"snippet":"We present mSLAM, a multilingual Speech and LAnguage Model that learns cross-lingual cross-modal representations of speech and text by pre-training jointly on large amounts of unlabeled speech and text in multiple languages. mSLAM combines w2v-BERT …","url":["https://arxiv.org/pdf/2202.01374"]}
+{"year":"2022","title":"MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages","authors":["GK Kumar, AS Gehlot, SS Mullappilly, K Nandakumar - arXiv preprint arXiv …, 2022","GKKAS Gehlot, SSMK Nandakumar - DravidianLangTech 2022, 2022"],"snippet":"Accuracy of English-language Question Answering (QA) systems has improved significantly in recent years with the advent of Transformer-based models (eg, BERT). These models are pre-trained in a self-supervised fashion with a large English text …","url":["https://aclanthology.org/2022.dravidianlangtech-1.pdf#page=33","https://arxiv.org/pdf/2204.05814"]}
+{"year":"2022","title":"Multi language Email Classification Using Transfer learning","authors":["MJC Sousa - 2022"],"snippet":"In recent years Artificial Intelligence has become a core part of many businesses, from manufacturers to service providers, AI can be found helping to improve business processes as well as providing customized experiences and support for …","url":["https://run.unl.pt/bitstream/10362/134446/1/TGI0525.pdf"]}
+{"year":"2022","title":"Multi-class sentiment analysis of urdu text using multilingual BERT","authors":["L Khan, A Amjad, N Ashraf, HT Chang - Scientific Reports, 2022"],"snippet":"Sentiment analysis (SA) is an important task because of its vital role in analyzing people’s opinions. However, existing research is solely based on the English language with limited work on low-resource languages. This study introduced a new …","url":["https://www.nature.com/articles/s41598-022-09381-9"]}
+{"year":"2022","title":"Multi-domain Neural Machine Translation","authors":["MQ Pham - 2021"],"snippet":"Today, neural machine translation (NMT) systems constitute state-of-the-art systems in machine translation. However, such translation models require relatively large train data and struggle to handle a specific domain text. A domain may consist of …","url":["https://tel.archives-ouvertes.fr/tel-03546910/document"]}
+{"year":"2022","title":"Multi-label Movie Genre Classification Using Multiple Modalities","authors":["DA LeBaron"],"snippet":"This project explores an ensemble approach to the task of multi-label movie genre classification. The proposed model combines data from movie posters, video trailer previews, text plot summaries, and metadata using separate deep networks. Other …","url":["http://cs230.stanford.edu/projects_fall_2021/reports/102983714.pdf"]}
+{"year":"2022","title":"Multi-level Distillation of Semantic Knowledge for Pre-training Multilingual Language Model","authors":["M Li, F Ding, D Zhang, L Cheng, H Hu, F Luo - arXiv preprint arXiv:2211.01200, 2022"],"snippet":"Pre-trained multilingual language models play an important role in cross-lingual natural language understanding tasks. However, existing methods did not focus on learning the semantic structure of representation, and thus could not optimize their …","url":["https://arxiv.org/pdf/2211.01200"]}
+{"year":"2022","title":"Multi-modal Chest X-Ray analysis: classification and report generation using self-supervised learning","authors":["N Brazzale - 2022"],"snippet":"Automated medical systems for classification, localization and diagnosis are increasingly being researched and developed. Accurate and automated disease detection is beneficial both to medical personnel, who do not have to perform …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/116259/master_Brazzale_Nicola_2022.pdf?sequence=1"]}
+{"year":"2022","title":"Multi-objective search for gender-fair and semantically correct word embeddings","authors":["M Hort, R Moussa, F Sarro - Applied Soft Computing, 2022"],"snippet":"Fairness is a crucial non-functional requirement of modern software systems that rely on the use of Artificial Intelligence (AI) to make decisions regarding our daily lives in application domains such as justice, healthcare and education. In fact, these …","url":["https://www.sciencedirect.com/science/article/pii/S1568494622009656"]}
+{"year":"2022","title":"Multi-source Multi-domain Sentiment Analysis with BERT-based Models","authors":["G Roccaruna"],"snippet":"… FEEL-IT, the other BERTbased model, is a sentiment classifier based on UmBERTo2, which inherits the RoBERTa architecture and is pre-trained on Commoncrawl ITA. FEEL-IT has only one head used for predicting positive and …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.62.pdf"]}
+{"year":"2022","title":"Multi-task learning for toxic comment classification and rationale extraction","authors":["KB Nelatoori, HB Kommanti - Journal of Intelligent Information Systems, 2022"],"snippet":"Social media content moderation is the standard practice as on today to promote healthy discussion forums. Toxic span prediction is helpful for explaining the toxic comment classification labels, thus is an important step towards building automated …","url":["https://link.springer.com/article/10.1007/s10844-022-00726-4"]}
+{"year":"2022","title":"Multi-Wiki90k: Multilingual Benchmark Dataset for Paragraph Segmentation","authors":["M Swędrowski, P Miłkowski, B Bojanowski, J Kocoń - Conference on Computational …, 2022"],"snippet":"In this paper, we present paragraph segmentation using cross-lingual knowledge transfer models. In our solution, we investigate the quality of multilingual models, such as mBERT and XLM-RoBERTa, as well as language independent models …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16210-7_11"]}
+{"year":"2022","title":"Multiaztertest@ Exist-Iberlef2022: Sexism Identification in Social Networks","authors":["K Bengoetxea, A Aguirregoitia - 2022"],"snippet":"The automatic identification of sexism and the categorization of the message in different types of sexism in social networks is the focus of the systems taking part in the EXIST-IberLEF 2022 shared task. Detecting online sexism and encouraging …","url":["http://ceur-ws.org/Vol-3202/exist-paper8.pdf"]}
+{"year":"2022","title":"Multidimensional tie strength and economic development","authors":["LM Aiello, S Joglekar, D Quercia - Scientific Reports, 2022"],"snippet":"The strength of social relations has been shown to affect an individual’s access to opportunities. To date, however, the correspondence between tie strength and population’s economic prospects has not been quantified, largely because of the …","url":["https://www.nature.com/articles/s41598-022-26245-4"]}
+{"year":"2022","title":"Multilingual and Multitarget Hate Speech Detection in Tweets","authors":["PCF Benamara, V Moriceau, MCGA Kumar"],"snippet":"Social media networks have become a space where users are free to relate their opinions and sentiments which may lead to a large spreading of hatred or abusive messages which have to be moderated. This paper proposes a supervised …","url":["https://www.academia.edu/download/83169351/66.pdf"]}
+{"year":"2022","title":"Multilingual Auxiliary Tasks Training: Bridging the Gap between Languages for Zero-Shot Transfer of Hate Speech Detection Models","authors":["S Montariol, A Riabi, D Seddah - arXiv preprint arXiv:2210.13029, 2022"],"snippet":"Zero-shot cross-lingual transfer learning has been shown to be highly challenging for tasks involving a lot of linguistic specificities or when a cultural gap is present between languages, such as in hate speech detection. In this paper, we highlight …","url":["https://arxiv.org/pdf/2210.13029"]}
+{"year":"2022","title":"Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-Translation","authors":["B Li, A Patel, C Callison-Burch, MS Rasooli - arXiv preprint arXiv:2209.02821, 2022"],"snippet":"… Some mined web data is available even for these low-resource languages, of which we use CommonCrawl and CC-100 datasets. … For the 8 test languages we draw from Common Crawl17 for {kk, gu, is} and CC-10018 for {my, ps, lv, ne, si}. …","url":["https://arxiv.org/pdf/2209.02821"]}
+{"year":"2022","title":"Multilingual fine-tuning for Grammatical Error Correction","authors":["K Pajak, D Pajak - Expert Systems with Applications, 2022"],"snippet":"… mT5 was pre-trained on a large mC4 dataset covering 101 languages and containing 26 TB of the Common Crawl web scrape. The model was pre-trained on the span corruption task, where consecutive spans of input tokens were replaced …","url":["https://www.sciencedirect.com/science/article/pii/S0957417422003773"]}
+{"year":"2022","title":"Multilingual Hate Speech Detection","authors":["V Lavrentiadou - 2022"],"snippet":"… It was trained on 100 languages, of a CommonCrawl Corpus, and it outperforms multilingual BERT on crosslingual classification. XLM-… The XLM-RoBERTa model, on the other hand, was trained on 2.5TB of filtered CommonCrawl data across 100 …","url":["https://ikee.lib.auth.gr/record/338409/files/GRI-2022-34410.pdf"]}
+{"year":"2022","title":"Multilingual hope speech detection in English and Dravidian languages","authors":["BR Chakravarthi - International Journal of Data Science and Analytics, 2022"],"snippet":"Recent work on language technology has aimed to identify negative language such as hate speech and cyberbullying as well as improve offensive language detection to mediate social media platforms. Most of these systems rely on using machine …","url":["https://link.springer.com/article/10.1007/s41060-022-00341-0"]}
+{"year":"2022","title":"Multilingual Language Model Adaptive Fine-Tuning: A Study on African Languages","authors":["JO Alabi, DI Adelani, M Mosbach, D Klakow - arXiv preprint arXiv:2204.06487, 2022"],"snippet":"Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks on both high resourced and low-resourced languages. However, there is still a large performance drop for languages unseen …","url":["https://arxiv.org/pdf/2204.06487"]}
+{"year":"2022","title":"Multilingual Name Entity Recognition and Intent Classification employing Deep Learning architectures","authors":["S Rizou, A Paflioti, A Theofilatos, A Vakali… - … Modelling Practice and …, 2022"],"snippet":"… For the fastText initialization we use a model which is pre-trained in Common Crawl and Wikipedia. … For the fastText initialization we used the model in Common Crawl and Wikipedia. For the GloVe initialization we used the 300 dimensional …","url":["https://www.sciencedirect.com/science/article/pii/S1569190X22000995"]}
+{"year":"2022","title":"Multilingual Natural Language Understanding for the FPT. AI Conversational Platform","authors":["P Le-Hong, TTL Nguyen, MT Pham, TH Vu - 2022 14th International Conference on …, 2022"],"snippet":"This paper presents a multilingual natural language understanding model which is based on BERT and ELECTRA neural networks. The model is pre-trained and fine-tuned on large datasets of four languages: Indonesian, Malaysian, Japanese and …","url":["https://ieeexplore.ieee.org/abstract/document/9953794/"]}
+{"year":"2022","title":"Multilingual Relation Classification via Efficient and Effective Prompting","authors":["Y Chen, D Harbecke, L Hennig - arXiv preprint arXiv:2210.13838, 2022"],"snippet":"Prompting pre-trained language models has achieved impressive performance on various NLP tasks, especially in low data regimes. Despite the success of prompting in monolingual settings, applying prompt-based methods in multilingual scenarios …","url":["https://arxiv.org/pdf/2210.13838"]}
+{"year":"2022","title":"Multilingual Representation Distillation with Contrastive Learning","authors":["W Tan, K Heffernan, H Schwenk, P Koehn - arXiv preprint arXiv:2210.05033, 2022"],"snippet":"Multilingual sentence representations from large models can encode semantic information from two or more languages and can be used for different cross-lingual information retrieval tasks. In this paper, we integrate contrastive learning into …","url":["https://arxiv.org/pdf/2210.05033"]}
+{"year":"2022","title":"Multilingual Sequence-to-Sequence Models for Hebrew NLP","authors":["M Eyal, H Noga, R Aharoni, I Szpektor, R Tsarfaty - arXiv preprint arXiv:2212.09682, 2022"],"snippet":"… 2021) in comparison, was trained on mC4, where its public replica1 is a 27TB collection of natural text in 101 languages drawn from the public Common Crawl, 66GB of which is Hebrew (4.125x more Hebrew training data compared to …","url":["https://arxiv.org/pdf/2212.09682"]}
+{"year":"2022","title":"Multilingual taxonomic text classification in an incremental number of languages","authors":["G CAMPESAN","N Navarin, G Campesan"],"snippet":"Taxonomic text classification is the Natural Language Processing (NLP) branch that aims at classifying text into a hierarchically organized schema. Its applications space from pure research to industrial and commercial purposes. In this thesis, in particular …","url":["https://thesis.unipd.it/bitstream/20.500.12608/36061/1/Campesan_Giulia.pdf","https://www.academia.edu/download/92194078/Campesan_Giulia.pdf"]}
+{"year":"2022","title":"Multilingual Transformer Encoders: a Word-Level Task-Agnostic Evaluation","authors":["F Gaschi, F Plesse, P Rastin, Y Toussaint - arXiv preprint arXiv:2207.09076, 2022"],"snippet":"… However, it could also be explained by the fact that mBERT is trained solely on Wikipedia whereas models like XLM-R are trained on the CommonCrawl corpus which might contain texts that are less comparable across languages. It is also to be …","url":["https://arxiv.org/pdf/2207.09076"]}
+{"year":"2022","title":"Multilingual Transformers for Product Matching--Experiments and a New Benchmark in Polish","authors":["A Wróblewska, S Tkachuk, S Łukasik - arXiv preprint arXiv:2205.15712, 2022"],"snippet":"… The authors of these studies extracted offers from websites collected under the CommonCrawl project.The selection of offers was based on the schema.org8 tags, which Internet sellers had started using in the last five … 7commoncrawl.org 8schema.org …","url":["https://arxiv.org/pdf/2205.15712"]}
+{"year":"2022","title":"Multilinguals at SemEval-2022 Task 11: Complex NER in Semantically Ambiguous Settings for Low Resource Languages","authors":["A Pandey, S Daw, N Unnam, V Pudi - Proceedings of the 16th International Workshop …, 2022"],"snippet":"We leverage pre-trained language models to solve the task of complex NER for two low-resource languages: Chinese and Spanish. We use the technique of Whole Word Masking (WWM) to boost the performance of masked language modeling …","url":["https://aclanthology.org/2022.semeval-1.201.pdf"]}
+{"year":"2022","title":"Multimodal Graph for Unaligned Multimodal Sequence Analysis via Graph Convolution and Graph Pooling","authors":["S Mai, S Xing, J He, Y Zeng, H Hu - ACM Transactions on Multimedia Computing …, 2022"],"snippet":"Multimodal sequence analysis aims to draw inferences from visual, language and acoustic sequences. A majority of existing works focus on the aligned fusion of three modalities to explore inter-modal interactions, which is impractical in real-world …","url":["https://dl.acm.org/doi/pdf/10.1145/3542927"]}
+{"year":"2022","title":"Multimodal sentiment analysis in real-life videos","authors":["L Stappen - 2022"],"snippet":"This thesis extends the emerging field of multimodal sentiment analysis of real-life videos, taking two components into consideration: the emotion and the emotion’s target. The emotion component of media is traditionally represented as a segment-based …","url":["https://opus.bibliothek.uni-augsburg.de/opus4/files/98988/Stappen_MultimodalSentimentAnalysisinReal-lifeVideos.pdf"]}
+{"year":"2022","title":"Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers","authors":["M Garg, S Wazarkar, M Singh, O Bojar"],"snippet":"With advancements in the methods of Natural Language Processing (NLP) by explicitly considering other modalities than just text, the resurgence of multimodal datasets has attracted significant attention. However, there remains lack of a …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.738.pdf"]}
+{"year":"2022","title":"Multitasking of sentiment detection and emotion recognition in code-mixed Hinglish data","authors":["S Ghosh, A Priyankar, A Ekbal, P Bhattacharyya - Knowledge-Based Systems, 2022"],"snippet":"As the number of non-native English speakers on social media has skyrocketed in recent years, sentiment and emotion analysis on regional languages and code-mixed data has gained traction. Despite extensive research on English, the area of Hindi-English …","url":["https://www.sciencedirect.com/science/article/pii/S0950705122012783"]}
+{"year":"2022","title":"MUST-VQA: MUltilingual Scene-text VQA","authors":["E Vivoli, AF Biten, A Mafla, D Karatzas, L Gomez - arXiv preprint arXiv:2209.06730, 2022"],"snippet":"… The mT5 model was trained on a 101-language Common Crawl-based multilingual variation. Only English Common Crawl is what T5 has been pre-trained on. Additionally an increase in performance is obtained by the use of GeGLU nonlinearities [31]. …","url":["https://arxiv.org/pdf/2209.06730"]}
+{"year":"2022","title":"Mutual Relation of Machine Translation and Quality Estimation","authors":["I Tryhubyshyn - 2022"],"snippet":"Machine Translation Quality Estimation predicts quality scores for translations produced by Machine Translation systems based on source and output segments. Quality Estimation systems are usually trained in a supervised manner using training …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/175591/120426924.pdf?sequence=1"]}
+{"year":"2022","title":"naab: A ready-to-use plug-and-play corpus for Farsi","authors":["S Sabouri, E Rahmati, S Gooran, H Sameti - arXiv preprint arXiv:2208.13486, 2022"],"snippet":"… 2020) in Farsi is a 70GB cleaned text corpus from a compilation of 8 (Common Crawl - fa (Crawl… 2022) or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the …","url":["https://arxiv.org/pdf/2208.13486"]}
+{"year":"2022","title":"NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis","authors":["SH Muhammad, DI Adelani, IS Ahmad, I Abdulmumin… - arXiv preprint arXiv …, 2022"],"snippet":"Sentiment analysis is one of the most widely studied applications in NLP, but most work focuses on languages with large amounts of data. We introduce the first large-scale human-annotated Twitter sentiment dataset for the four most widely spoken …","url":["https://arxiv.org/pdf/2201.08277"]}
+{"year":"2022","title":"NamedEntityRangers at SemEval-2022 Task 11: Transformer-based Approaches for Multilingual Complex Named Entity Recognition","authors":["A Miftahova, A Pugachev, A Skiba, K Artemova… - Proceedings of the 16th …, 2022"],"snippet":"This paper presents the two submissions of NamedEntityRangers Team to the MultiCoNER Shared Task, hosted at SemEval-2022. We evaluate two state-of-the-art approaches, of which both utilize pre-trained multi-lingual language models …","url":["https://aclanthology.org/2022.semeval-1.216.pdf"]}
+{"year":"2022","title":"NapierOne: A modern mixed file data set alternative to Govdocs1","authors":["SR Davies, R Macfarlane, WJ Buchanan - Forensic Science International: Digital …, 2022"],"snippet":"It was found when reviewing the ransomware detection research literature that almost no proposal provided enough detail on how the test data set was created, or sufficient description of its actual content, to allow it to be recreated by other …","url":["https://arxiv.org/pdf/2201.08154"]}
+{"year":"2022","title":"Natural Language Correction With Focus on Czech","authors":["J Náplava - 2022"],"snippet":"Natural language correction, a subfield of natural language processing (NLP), is the task of automatically correcting user errors in written texts. It includes, but is not limited to, grammatical error correction, spelling error correction and diacritics …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/174730/140102103.pdf?sequence=1"]}
+{"year":"2022","title":"Natural Language Inference with Self-Attention for Veracity Assessment of Pandemic Claims","authors":["M Arana-Catania, E Kochkina, A Zubiaga, M Liakata… - arXiv preprint arXiv …, 2022"],"snippet":"… on the health domain focused on information retrieval from general websites through the Common Crawl corpus (commoncrawl.org). … Research challenge using claims on the health domain focused on information retrieval from general …","url":["https://arxiv.org/pdf/2205.02596"]}
+{"year":"2022","title":"Natural Language Processing in toxicology: Delineating Adverse Outcome Pathways and guiding the application of New Approach Methodologies","authors":["MPF Corradi, AM de Haan, B Staumont, AH Piersma… - Biomaterials and …, 2022"],"snippet":"Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiating event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a …","url":["https://www.sciencedirect.com/science/article/pii/S266653442200023X"]}
+{"year":"2022","title":"Natural Questions in Icelandic","authors":["V Snæbjarnarson, H Einarsson"],"snippet":"We present the first extractive question answering (QA) dataset for Icelandic, Natural Questions in Icelandic (NQiI). Developing such datasets is important for the development and evaluation of Icelandic QA systems. It also aids in the …","url":["https://vesteinn.is/uploads/snaebjarnarson2022natural.pdf"]}
+{"year":"2022","title":"Navigable Proximity Graph-Driven Native Hybrid Queries with Structured and Unstructured Constraints","authors":["M Wang, L Lv, X Xu, Y Wang, Q Yue, J Ni - arXiv preprint arXiv:2203.13601, 2022"],"snippet":"As research interest surges, vector similarity search is applied in multiple fields, including data mining, computer vision, and information retrieval. {Given a set of objects (eg, a set of images) and a query object, we can easily transform each object …","url":["https://arxiv.org/pdf/2203.13601"]}
+{"year":"2022","title":"Need for Wheel Speed: Generating synthetic wheel speeds using LSTM and GANs","authors":["E Berglund - 2022"],"snippet":"… One of the largest data sets available is Common crawl 1 which consists of over 5 Peta Bytes of data in total which is huge amounts of data, and it grows consistently with around 300 Tebibyte of data every two months. At this rate, it will take close to …","url":["https://www.diva-portal.org/smash/get/diva2:1694797/FULLTEXT01.pdf"]}
+{"year":"2022","title":"Nepali Encoder Transformers","authors":["U Maskey, M Bhatta, SR Bhatta, S Dhungel, BK Bal"],"snippet":"… ● XLM-RoBERTa: XLM-RoBERTa (Conneau et al., 2020) is a multi-lingual model that is trained on large dataset of filtered CommonCrawl data covering 100 languages. …","url":["https://sigul-2022.ilc.cnr.it/wp-content/uploads/2022/10/Nepali-Encoder-Transformers.pdf"]}
+{"year":"2022","title":"NER in Hindi Language Using Transformer Model: XLM-Roberta","authors":["AA Choure, RB Adhao, VK Pachghare - 2022 IEEE International Conference on …, 2022"],"snippet":"… It has been pre-trained on 2.5 TB of filtered Common-Crawl data with hundred languages. It was pre-trained with the Masked language modeling (MLM) goal. Taking a sentence as an example, the model masks 15% of the words in the input at …","url":["https://ieeexplore.ieee.org/abstract/document/9935841/"]}
+{"year":"2022","title":"NerKor+ Cars-OntoNotes+","authors":["A Novák, B Novák"],"snippet":"In this paper, we present an upgraded version of the Hungarian NYTK-NerKor named entity corpus, which contains about twice as many annotated spans and 7 times as many distinct entity types as the original version. We used an extended …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.203.pdf"]}
+{"year":"2022","title":"Net impact of large language models trained on code","authors":["P Gherciu - … tehnico-ştiinţifică a studenţilor, masteranzilor şi …, 2022"],"snippet":"Natural language processing has seen many improvements in recent years, particularly driven by machine learning models such as OpenAI’s GPT-3. This paper aims to present the various language models, as well as OpenAI Codex, which is …","url":["https://ibn.idsi.md/sites/default/files/imag_file/p-189-192.pdf"]}
+{"year":"2022","title":"Neural Approaches to Conversational Information Retrieval","authors":["J Gao, C Xiong, P Bennett, N Craswell - arXiv preprint arXiv:2201.05176, 2022"],"snippet":"A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with the system to seek information via multi-turn conversations of natural language, in spoken or …","url":["https://arxiv.org/pdf/2201.05176"]}
+{"year":"2022","title":"Neural Language Models as What If?-Engines for HCI Research","authors":["P Hämäläinen, M Tavast, A Kunnari - 27th International Conference on Intelligent …, 2022"],"snippet":"Collecting data is one of the bottlenecks of Human-Computer Interaction (HCI) and user experience (UX) research. In this poster paper, we explore and critically evaluate the potential of large-scale neural language models like GPT-3 in …","url":["https://dl.acm.org/doi/abs/10.1145/3490100.3516458"]}
+{"year":"2022","title":"Neural machine translation for Hungarian","authors":["LJ Laki, ZG Yang - Acta Linguistica Academica, 2022"],"snippet":"In the scope of this research, we aim to give an overview of the currently existing solutions for machine translation and we assess their performance on the English-Hungarian language pair. Hungarian is considered to be a challenging language for machine …","url":["https://akjournals.com/view/journals/2062/aop/article-10.1556-2062.2022.00576/article-10.1556-2062.2022.00576.xml"]}
+{"year":"2022","title":"Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning","authors":["E Erdem, M Kuyu, S Yagcioglu, A Frank…"],"snippet":"Developing artificial learning systems that can understand and generate natural language has been one of the long-standing goals of artificial intelligence. Recent decades have witnessed an impressive progress on both of these problems, giving …","url":["https://web.cs.hacettepe.edu.tr/~erkut/publications/nnlg-survey.pdf"]}
+{"year":"2022","title":"Neural text summarization for Hungarian","authors":["ZG Yang - Acta Linguistica Academica, 2022"],"snippet":"… One of the most prominent representative dataset in this category is the Common Crawl. However, despite the fact that web scraping can give rise to large datasets, the filtering and the cleaning of data can be still challenging and often claimed as a …","url":["https://akjournals.com/view/journals/2062/aop/article-10.1556-2062.2022.00577/article-10.1556-2062.2022.00577.xml"]}
+{"year":"2022","title":"Neural Transfer Learning For Vietnamese Sentiment Analysis Using Pre-trained Contextual Language Models","authors":["AP Le, TV Pham, TV Le, DV Huynh - 2021 IEEE International Conference on Machine …, 2021"],"snippet":"We propose a fine-tuning methodology and a comprehensive comparison between state-of-the-art pre-trained language models (PLM) when applying to Vietnamese Sentiment Analysis. The fine-tuning architecture includes three main components: (1) …","url":["https://ieeexplore.ieee.org/abstract/document/9690554/"]}
+{"year":"2022","title":"New directions in empirical asset pricing: information, innovation, and stock returns","authors":["J Vahl - 2022"],"snippet":"This dissertation is a collection of three essays that explore new directions in empirical asset pricing. The first essay studies the role of textual information in analyst reports. I show that analysts use the report text to convey soft information that …","url":["https://open.library.ubc.ca/media/download/pdf/24/1.0417337/4"]}
+{"year":"2022","title":"New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology","authors":["S Nath, A Marie, S Ellershaw, E Korot, PA Keane - British Journal of Ophthalmology, 2022"],"snippet":"Natural language processing (NLP) is a subfield of machine intelligence focused on the interaction of human language with computer systems. NLP has recently been discussed in the mainstream media and the literature with the advent of Generative …","url":["https://bjo.bmj.com/content/early/2022/05/06/bjophthalmol-2022-321141.abstract"]}
+{"year":"2022","title":"New Methods and the Study of Vulnerable Groups: Using Machine Learning to Identify Immigrant-Oriented Nonprofit Organizations","authors":["C Ren, I Bloemraad - Socius, 2022"],"snippet":"Many migrants are vulnerable due to noncitizenship, linguistic or cultural barriers, and inadequate safety-net infrastructures. Immigrant-oriented nonprofits can play an important role in improving immigrant well-being. However, progress on …","url":["https://journals.sagepub.com/doi/pdf/10.1177/23780231221076992"]}
+{"year":"2022","title":"News Article Classification using a Transfer Learning Approach","authors":["K Abhishek - 2022 10th International Conference on Reliability …, 2022"],"snippet":"The increasing proliferation of electronic files in recent decades has been addressed by significant improvements in Natural Language Processing. As the text data generated is quite large, employing sophisticated algorithms that can process …","url":["https://ieeexplore.ieee.org/abstract/document/9965142/"]}
+{"year":"2022","title":"NLI Models for Assessing Facticity in Summarization Methods","authors":["BJ Dusil - 2022"],"snippet":"Guidelines: The task is to: 1) Research state-of-the-art NLP approaches for text summarization, focusing on evaluation methods for assessment of generated summaries. Explore mainly model-based approaches. 2) Discuss available options …","url":["https://wiki.control.fel.cvut.cz/mediawiki/images/8/88/Dp_2022_dusil_jan.pdf"]}
+{"year":"2022","title":"NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measures","authors":["J Vamvas, R Sennrich - arXiv preprint arXiv:2204.13692, 2022"],"snippet":"Being able to rank the similarity of short text segments is an interesting bonus feature of neural machine translation. Translation-based similarity measures include direct and pivot translation probability, as well as translation cross-likelihood, which …","url":["https://arxiv.org/pdf/2204.13692"]}
+{"year":"2022","title":"No Language Left Behind: Scaling Human-Centered Machine Translation","authors":["N Team, MR Costa-jussà, J Cross, O Çelebi…"],"snippet":"Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today. However, such efforts have coalesced around a small subset of languages, leaving …","url":["https://arxiv.org/pdf/2207.04672"]}
+{"year":"2022","title":"No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media","authors":["M Spliethöver, M Keiff, H Wachsmuth - arXiv preprint arXiv:2211.03634, 2022"],"snippet":"… (2021), we collected news articles from Common Crawl3. Since the media bias rating history is not available, we mapped each outlet to its current rating. To extract the pure text from the collected files in WARC format, we used the library news-please …","url":["https://arxiv.org/pdf/2211.03634"]}
+{"year":"2022","title":"Noise Reduction Learning based on XLNet-CRF for Biomedical Named Entity Recognition","authors":["Z Chai, H Jin, S Shi, S Zhan, L Zhuo, Y Yang, Q Lian - IEEE/ACM Transactions on …, 2022"],"snippet":"In recent years, Biomedical Named Entity Recognition (BioNER) systems have mainly been based on deep neural networks, which are used to extract information from the rapidly expanding biomedical literature. Long-distance context …","url":["https://ieeexplore.ieee.org/abstract/document/9730067/"]}
+{"year":"2022","title":"Noise-Reduction for Automatically Transferred Relevance Judgments","authors":["M Fröbe, C Akiki, M Potthast, M Hagen"],"snippet":"The TREC Deep Learning tracks used MS MARCO Version 1 as their official training data until 2020 and switched to Version 2 in 2021. For Version 2, all previously judged documents were re-crawled. Interestingly, in the track’s 2021 edition, models …","url":["https://webis.de/downloads/publications/papers/froebe_2022d.pdf"]}
+{"year":"2022","title":"Nominalizations with the suffixes-ee and-ation A distributional semantic analysis","authors":["V Schneider, I Plag"],"snippet":"… • FastText Common Crawl subword model (Bojanowski et al. 2016, Mikolov et al. 2018) … • FastText Common Crawl subword model (Bojanowski et al. 2016, Mikolov et al. 2018) … • FastText Common Crawl subword model (Bojanowski et al. 2016 …","url":["https://frames.phil.uni-duesseldorf.de/wp-content/uploads/2022/11/InSemantic22_Schneider.pdf"]}
+{"year":"2022","title":"Non-Autoregressive Machine Translation: It's Not as Fast as it Seems","authors":["J Helcl, B Haddow, A Birch - arXiv preprint arXiv:2205.01966, 2022"],"snippet":"Efficient machine translation models are commercially important as they can increase inference speeds, and reduce costs and carbon emissions. Recently, there has been much interest in non-autoregressive (NAR) models, which promise faster …","url":["https://arxiv.org/pdf/2205.01966"]}
+{"year":"2022","title":"Normalization and Attention","authors":["JC Ye - Geometry of Deep Learning, 2022"],"snippet":"… Sixty percent of the training data set comes from a filtered version of Common Crawl consisting of 410 billion tokens. Other sources are 19 billion tokens from WebText2, 12 billion tokens from Books1, 55 billion tokens from Books2, and 3 …","url":["https://link.springer.com/chapter/10.1007/978-981-16-6046-7_9"]}
+{"year":"2022","title":"NT5 at WMT 2022 General Translation Task","authors":["M Morishita, K Kudo, Y Oka, K Chousa, S Kiyono…"],"snippet":"… Monolingual Corpus We also used the following provided monolingual data: News Crawl, News Commentary, and Common Crawl. We backtranslated the monolingual sentences with a targetto-source model trained only with the provided …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.25.pdf"]}
+{"year":"2022","title":"NULL at SemEval-2022 Task 6: Intended Sarcasm Detection Using Stylistically Fused Contextualized Representation and Deep Learning","authors":["M Rahgouy, HB Giglou, T Rahgooy, C Seals - … of the 16th International Workshop on …, 2022"],"snippet":"… ), which is pre-trained on 2.5TB of CommonCrawl data containing 100 languages. The model learns an inner representation of 100 languages that can then be used to extract features useful for downstream tasks. The function CE ∈ R768 is a base …","url":["https://aclanthology.org/2022.semeval-1.120.pdf"]}
+{"year":"2022","title":"NUS-IDS at CheckThat! 2022: Identifying Check-worthiness of Tweets using CheckthaT5","authors":["M Du, SD Gollapalli, SK Ng - Working Notes of CLEF, 2022"],"snippet":"This paper describes our system CheckthaT5, which was designed in the context of the Checkthat! 2022 competition at CLEF. CheckthaT5 explores the feasibility of adapting sequence-to-sequence models for detecting check-worthy social media …","url":["http://ceur-ws.org/Vol-3180/paper-36.pdf"]}
+{"year":"2022","title":"NusaCrowd: Open Source Initiative for Indonesian NLP Resources","authors":["S Cahyawijaya, H Lovenia, AF Aji, GI Winata, B Wilie… - arXiv preprint arXiv …, 2022"],"snippet":"We present NusaCrowd, a collaborative initiative to collect and unite existing resources for Indonesian languages, including opening access to previously non-public resources. Through this initiative, we have has brought together 137 datasets and …","url":["https://arxiv.org/pdf/2212.09648"]}
+{"year":"2022","title":"OCHADAI at SemEval-2022 Task 2: Adversarial Training for Multilingual Idiomaticity Detection","authors":["LK Pereira, I Kobayashi - arXiv preprint arXiv:2206.03025, 2022"],"snippet":"We propose a multilingual adversarial training model for determining whether a sentence contains an idiomatic expression. Given that a key challenge with this task is the limited size of annotated data, our model relies on pre-trained contextual …","url":["https://arxiv.org/pdf/2206.03025"]}
+{"year":"2022","title":"OcWikiDisc: a Corpus of Wikipedia Talk Pages in Occitan","authors":["A Miletić, Y Scherrer - Proceedings of the Ninth Workshop on NLP for Similar …, 2022"],"snippet":"This paper presents OcWikiDisc, a new freely available corpus in Occitan, as well as language identification experiments on Occitan done as part of the corpus building process. Occitan is a regional language spoken mainly in the south of France and in …","url":["https://aclanthology.org/2022.vardial-1.8.pdf"]}
+{"year":"2022","title":"Odor Descriptor Understanding through Prompting","authors":["L Sisson - arXiv preprint arXiv:2205.03719, 2022"],"snippet":"Embeddings from contemporary natural language processing (NLP) models are commonly used as numerical representations for words or sentences. However, odor descriptor words, like \"leather\" or \"fruity\", vary significantly between their …","url":["https://arxiv.org/pdf/2205.03719"]}
+{"year":"2022","title":"Offensive language detection in Tamil YouTube comments by adapters and cross-domain knowledge transfer","authors":["M Subramanian, R Ponnusamy, S Benhur… - Computer Speech & …, 2022"],"snippet":"… XLM-RoBERTa is a self-supervised transformer model that has been pre-trained on 2.5TB of filtered CommonCrawl data from 100 languages. This model does not require lang tensors to understand which language is being used, and it should be …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000407"]}
+{"year":"2022","title":"Offensive Language Detection in Turkish Twitter Data with BERT Models","authors":["A Özberk - 2022"],"snippet":"As insulting statements become more frequent on online platforms, these negative statements create a reaction and disturb the peace of society. Identifying these expressions as early as possible is important to protect the victims. Offensive …","url":["http://www.openaccess.hacettepe.edu.tr:8080/xmlui/bitstream/handle/11655/26131/OFFENSIVE%20LANGUAGE%20DETECTION%20IN%20TURKISH%20TWITTER%20DATA%20WITH%20BERT%20MODELS.pdf?sequence=1"]}
+{"year":"2022","title":"On Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making","authors":["J Schoeffer, M De-Arteaga, N Kuehl - arXiv preprint arXiv:2209.11812, 2022"],"snippet":"Explanations have been framed as an essential feature for better and fairer human-AI decision-making. In the context of fairness, this has not been appropriately studied, as prior works have mostly evaluated explanations based on their effects on …","url":["https://arxiv.org/pdf/2209.11812"]}
+{"year":"2022","title":"On Systematic Style Differences between Unsupervised and Supervised MT and an Application for High-Resource Machine Translation","authors":["K Marchisio, M Freitag, D Grangier"],"snippet":"Modern unsupervised machine translation (MT) systems reach reasonable translation quality under clean and controlled data conditions. As the performance gap between supervised and unsupervised MT narrows, it is interesting to ask …","url":["https://openreview.net/pdf?id=rqlQknbB-5"]}
+{"year":"2022","title":"On the Applicability of Zero-Shot Cross-Lingual Transfer Learning for Sentiment Classification in Distant Language Pairs","authors":["A Rusli, M Shishido"],"snippet":"This research explores the applicability of cross-lingual transfer learning from English to Japanese and Indonesian using the XLM-R pre-trained model. The results are compared with several previous works, either by models using a similar …","url":["https://www.anlp.jp/proceedings/annual_meeting/2022/pdf_dir/A6-1.pdf"]}
+{"year":"2022","title":"On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model","authors":["S Shin, SW Lee, H Ahn, S Kim, HS Kim, B Kim, K Cho… - arXiv preprint arXiv …, 2022"],"snippet":"Many recent studies on large-scale language models have reported successful in-context zeroand few-shot learning ability. However, the in-depth analysis of when in-context learning occurs is still lacking. For example, it is unknown how in-context learning …","url":["https://arxiv.org/pdf/2204.13509"]}
+{"year":"2022","title":"On the Effectiveness of Quasi Character-Level Models for Machine Translation","authors":["S Carrión-Ponz, F Casacuberta - Proceedings of the 15th biennial conference of the …, 2022"],"snippet":"Neural Machine Translation (NMT) models often use subword-level vocabularies to deal with rare or unknown words. Although some studies have shown the effectiveness of purely character-based models, these approaches have resulted in …","url":["https://aclanthology.org/2022.amta-research.10.pdf"]}
+{"year":"2022","title":"On the Geometry of Concreteness","authors":["C Wartena - Proceedings of the 7th Workshop on Representation …, 2022"],"snippet":"… For English we use the 300 dimensional fastText embeddings without subword information trained on the Common Crawl with 600 billion tokens. For German we also use 300 dimensional fastText embeddings trained on the Common Crawl and …","url":["https://aclanthology.org/2022.repl4nlp-1.21.pdf"]}
+{"year":"2022","title":"On the Role of Bidirectionality in Language Model Pre-Training","authors":["M Artetxe, J Du, N Goyal, L Zettlemoyer, V Stoyanov - arXiv preprint arXiv:2205.11726, 2022"],"snippet":"Prior work on language model pre-training has explored different architectures and learning objectives, but differences in data, hyperparameters and evaluation make a principled comparison difficult. In this work, we focus on bidirectionality as a key …","url":["https://arxiv.org/pdf/2205.11726"]}
+{"year":"2022","title":"On the Surrogate Gap between Contrastive and Supervised Losses","authors":["H Bao, Y Nagano, K Nozawa - International Conference on Machine Learning, 2022"],"snippet":"Contrastive representation learning encourages data representation to make semantically similar pairs closer than randomly drawn negative samples, which has been successful in various domains such as vision, language, and graphs. Recent …","url":["https://proceedings.mlr.press/v162/bao22e/bao22e.pdf"]}
+{"year":"2022","title":"One Document, Many Revisions: A Dataset for Classification and Description of Edit Intents","authors":["D Rajagopal, X Zhang, M Gamon, S Jauhar, D Yang…"],"snippet":"… It is important to note that BART was pretrained on written text over the C4 commoncrawl corpus6. And adapting it to wikipedia comment generation task did not directly lead to performance gains. Our experiments show that pretrained BART …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.591.pdf"]}
+{"year":"2022","title":"Online patient feedback as a safety valve: An automated language analysis of unnoticed and unresolved safety incidents","authors":["A Gillespie, TW Reader - Risk Analysis, 2022"],"snippet":"… Specifically, we used a publicly available language model created from the Common Crawl dataset of webpages, comprising 684,831 unique vectors represented in 300 dimensions (Explosion, 2020). While word embeddings trained on medical texts …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.14002"]}
+{"year":"2022","title":"Online Social Networks and Media","authors":["JSL Figuerêdo, ALLM Maia, RT Calumby"],"snippet":"Depression is a challenge to public health, frequently related to disability and one of the reasons that lead to suicide. Many of the ones who suffer depression use social media to obtain information or even to talk about their problem. Some studies have …","url":["https://e-tarjome.com/storage/panel/fileuploads/2022-08-14/1660480282_e17068.pdf"]}
+{"year":"2022","title":"Open-domain conversational search assistants: the Transformer is all you need","authors":["R Ferreira, M Leite, D Semedo, J Magalhaes - Information Retrieval Journal, 2022"],"snippet":"On the quest of providing a more natural interaction between users and search systems, open-domain conversational search assistants have emerged, by assisting users in answering questions about open topics in a conversational manner. In this …","url":["https://link.springer.com/article/10.1007/s10791-022-09403-0"]}
+{"year":"2022","title":"OPT: Open Pre-trained Transformer Language Models","authors":["S Zhang, S Roller, N Goyal, M Artetxe, M Chen, S Chen… - arXiv preprint arXiv …, 2022"],"snippet":"… All corpora were previously collected or filtered to contain predominantly English text, but a small amount of non-English data is still present within the corpus via CommonCrawl. We removed duplicated documents across all datasets by filtering …","url":["https://arxiv.org/pdf/2205.01068"]}
+{"year":"2022","title":"Optimize_Prime@ DravidianLangTech-ACL2022: Abusive Comment Detection in Tamil","authors":["S Patankar, O Gokhale, O Litake, A Mandke, D Kadam - arXiv preprint arXiv …, 2022"],"snippet":"This paper tries to address the problem of abusive comment detection in low-resource indic languages. Abusive comments are statements that are offensive to a person or a group of people. These comments are targeted toward individuals belonging to …","url":["https://arxiv.org/pdf/2204.09675"]}
+{"year":"2022","title":"Optimize_Prime@ DravidianLangTech-ACL2022: Emotion Analysis in Tamil","authors":["O Gokhale, S Patankar, O Litake, A Mandke, D Kadam - arXiv preprint arXiv …, 2022"],"snippet":"This paper aims to perform an emotion analysis of social media comments in Tamil. Emotion analysis is the process of identifying the emotional context of the text. In this paper, we present the findings obtained by Team Optimize_Prime in the ACL 2022 …","url":["https://arxiv.org/pdf/2204.09087"]}
+{"year":"2022","title":"ORCA: A Challenging Benchmark for Arabic Language Understanding","authors":["AR Elmadany, EMB Nagoudi, M Abdul-Mageed - arXiv preprint arXiv:2212.10758, 2022"],"snippet":"… 2020b) is a transformerbased multilingual masked language model pretrained on more than 2TB of filtered CommonCrawl data in 100 languages, including Arabic (2.9B tokens). XLM-R uses a Transformer model trained a multilingual version of masked …","url":["https://arxiv.org/pdf/2212.10758"]}
+{"year":"2022","title":"Ordvektorer i lexikografiskt arbete","authors":["M Forsberg, E Sköldberg - LIVE and LEARN"],"snippet":"… Ordvektorerna är baserade på datamängden Common Crawl, som är ett stort insamlat material med webbsidor, och Wikipedia. Det finns en rik flora av vetenskapliga arbeten som kretsar runt hur frukten av lexikografiskt arbete kan …","url":["https://gupea.ub.gu.se/bitstream/handle/2077/74254/GU-ISS-2022-03%20Lars%20Borin%20Festskrift%20Digital%20publicering%20221121.pdf?sequence=1&isAllowed=y#page=51"]}
+{"year":"2022","title":"Out-of-Distribution Detection and Selective Generation for Conditional Language Models","authors":["J Ren, J Luo, Y Zhao, K Krishna, M Saleh… - arXiv preprint arXiv …, 2022"],"snippet":"Machine learning algorithms typically assume independent and identically distributed samples in training and at test time. Much work has shown that high-performing ML classifiers can degrade significantly and provide overly-confident, wrong …","url":["https://arxiv.org/pdf/2209.15558"]}
+{"year":"2022","title":"Overview of HIPE-2022: Named Entity Recognition and Linking in Multilingual Historical Documents","authors":["A Doucet, S Clematide - … IR Meets Multilinguality, Multimodality, and Interaction …, 2022","M Ehrmann, M Romanello, S Najem-Meyer, A Doucet… - International Conference of …, 2022","S Clematide"],"snippet":"This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places and other Entities), a shared task on named entity recognition and linking in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=LzaFEAAAQBAJ&oi=fnd&pg=PA423&dq=commoncrawl&ots=LmT-NMkkn2&sig=Q_jxi2Mi1rvfcsodMOiSk1LYkXY","https://hipe-eval.github.io/HIPE-2022/assets/pdf/HIPE_2022_LNCS_CondensedLabOverview_accepted_version.pdf","https://link.springer.com/chapter/10.1007/978-3-031-13643-6_26"]}
+{"year":"2022","title":"Overview of NTCIR-16","authors":["T Yamamoto, Z Dou","Z Dou, T Yamamoto"],"snippet":"… Chuweb21 is a subset of the Common Crawl dataset and it contains 3,402,457 domains and 858,616,203 web pages. Secondly, two versions of relevance assessment are introduced: the Gold version given by the topic creators, and the …","url":["https://research.nii.ac.jp/ntcir/workshop/OnlineProceedings16/pdf/ntcir/01-NTCIR16-OV-YamamotoT-slides.pdf","https://research.nii.ac.jp/ntcir/workshop/OnlineProceedings16/pdf/ntcir/01-NTCIR16-OV-YamamotoT.pdf"]}
+{"year":"2022","title":"Overview of the 2022 BUCC Shared Task: Bilingual Term Alignment in Comparable Specialized Corpora","authors":["O Adjali, E Morin, S Sharoff, R Rapp, P Zweigenbaum - LREC 2022 Workshop …, 2022"],"snippet":"The BUCC 2022 shared task addressed bilingual terminology alignment in comparable corpora. Many research groups are working on this problem using a wide variety of approaches. However, as there is no standard way to measure the …","url":["https://comparable.limsi.fr/bucc2022/BUCC2022-proceedings-20220617.pdf#page=77"]}
+{"year":"2022","title":"Overview of Touché 2022: Argument Retrieval","authors":["A Bondarenko, M Fröbe, J Kiesel, S Syed, T Gurcke… - 2022","T Gurcke, M Beloucif, A Panchenko, C Biemann… - Experimental IR Meets …, 2022"],"snippet":"This paper is a report on the third year of the Touché lab on argument retrieval hosted at CLEF 2022. With the goal of supporting and promoting the research and development of new technologies for argument mining and argument analysis, we …","url":["http://ceur-ws.org/Vol-3180/paper-247.pdf","https://books.google.de/books?hl=en&lr=lang_en&id=LzaFEAAAQBAJ&oi=fnd&pg=PA311&dq=commoncrawl&ots=LmT-NMkkn2&sig=yArB4HgQifPyU4Ny0t18ZGgSD1E"]}
+{"year":"2022","title":"PANGUBOT: Efficient Generative Dialogue Pre-training from Pre-trained Language Model","authors":["F Mi, Y Li, Y Zeng, J Zhou, Y Wang, C Xu, L Shang… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper, we introduce PANGUBOT, a Chinese pre-trained open-domain dialogue generation model based on a large pre-trained language model (PLM) PANGU-alpha (Zeng et al.,2021). Different from other pre-trained dialogue models …","url":["https://arxiv.org/pdf/2203.17090"]}
+{"year":"2022","title":"Papago's Submission for the WMT21 Quality Estimation Shared Task","authors":["S Lim, H Kim, H Kim - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"This paper describes Papago submission to the WMT 2021 Quality Estimation Task 1: Sentence-level Direct Assessment. Our multilingual Quality Estimation system explores the combination of Pretrained Language Models and Multi-task Learning …","url":["https://aclanthology.org/2021.wmt-1.98.pdf"]}
+{"year":"2022","title":"Paragraph-based Transformer Pre-training for Multi-Sentence Inference","authors":["L Di Liello, S Garg, L Soldaini, A Moschitti - arXiv preprint arXiv:2205.01228, 2022"],"snippet":"Inference tasks such as answer sentence selection (AS2) or fact verification are typically solved by fine-tuning transformer-based models as individual sentence-pair classifiers. Recent studies show that these tasks benefit from modeling …","url":["https://arxiv.org/pdf/2205.01228"]}
+{"year":"2022","title":"Parameter-efficient feature-based transfer for paraphrase identification","authors":["X Liu, R Rzepka, K Araki - Natural Language Engineering, 2022"],"snippet":"There are many types of approaches for Paraphrase Identification (PI), an NLP task of determining whether a sentence pair has equivalent semantics. Traditional approaches mainly consist of unsupervised learning and feature engineering, which …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/parameterefficient-featurebased-transfer-for-paraphrase-identification/D587AA786E0B7F21AD61651E29551FE4"]}
+{"year":"2022","title":"Parameter-efficient Zero-shot Transfer for Cross-Language Dense Retrieval with Adapters","authors":["E Yang, S Nair, D Lawrie, J Mayfield, DW Oard - arXiv preprint arXiv:2212.10448, 2022"],"snippet":"A popular approach to creating a zero-shot cross-language retrieval model is to substitute a monolingual pretrained language model in the retrieval model with a multilingual pretrained language model such as Multilingual BERT. This multilingual …","url":["https://arxiv.org/pdf/2212.10448"]}
+{"year":"2022","title":"Parliamentary representative behaviour in times of crisis: a comparative perspective with a focus on Greece and the Eurozone crisis","authors":["EI Kartalis - 2022"],"snippet":"Much scholarly discussion has been devoted to the impact of the 2009 Eurozone economic Crisis on the functioning of European democracies. Especially for those countries that bailout agreements had to be implemented in, the literature has …","url":["https://repositorio.ul.pt/bitstream/10451/55162/1/PhDThesis_Final_Kartalis.pdf"]}
+{"year":"2022","title":"Parquet Containers","authors":["M Coscia, A Weber - 2022"],"snippet":"Archives preserve content and support various types of analysis, study, and use. Archiving the Web and social media (eg, Twitter) content involves use of representations like Web ARChive (WARC) and JavaScript Object Notation (JSON) …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/109995/ParquetContainersReport.pdf?sequence=2&isAllowed=y"]}
+{"year":"2022","title":"Partitioning Trillion-Edge Graphs","authors":["GM Slota, K Devine, K Madduri, S Rajamanickam - Massive Graph Analytics"],"snippet":"Graph partitioning is a key preprocessing step for distributed-memory graph analytics and scientific computations on meshes. This chapter introduces XtraPuLP, a new distributed-memory graph partitioner designed to process trillion-edge graphs …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003033707-12/partitioning-trillion-edge-graphs-george-slota-karen-devine-kamesh-madduri-sivasankaran-rajamanickam"]}
+{"year":"2022","title":"Pełen tekst","authors":["T Harting, S Mesbah, C Lofi"],"snippet":"… For the language-individual model, we use FastText word em-beddings [11] which are trained on Common Crawl and Wikipedia dataset. For the language-consistent model, we use pre-trained mul-tilingual embeddings which are released by FastText …","url":["https://9lib.org/document/wyejx8rz-lorem.html"]}
+{"year":"2022","title":"Perplexed by Quality: A Perplexity-based Method for Adult and Harmful Content Detection in Multilingual Heterogeneous Web Data","authors":["T Jansen, Y Tong, V Zevallos, PO Suarez - arXiv preprint arXiv:2212.10440, 2022"],"snippet":"As demand for large corpora increases with the size of current state-of-the-art language models, using web data as the main part of the pre-training corpus for these models has become a ubiquitous practice. This, in turn, has introduced an …","url":["https://arxiv.org/pdf/2212.10440"]}
+{"year":"2022","title":"Personalized filled-pause generation with group-wise prediction models","authors":["Y Matsunaga, T Saeki, S Takamichi, H Saruwatari - arXiv preprint arXiv:2203.09961, 2022"],"snippet":"In this paper, we propose a method to generate personalized filled pauses (FPs) with group-wise prediction models. Compared with fluent text generation, disfluent text generation has not been widely explored. To generate more human-like texts …","url":["https://arxiv.org/pdf/2203.09961"]}
+{"year":"2022","title":"Perspectives on the Cognitive Unconscious","authors":["AS Reber, R Allen"],"snippet":"My interest in nonconscious processes goes back to my youth when I imagined that Sigmund Freud had discovered all that there was to be known about the human mind. But interest in the nonconscious and the role it plays in mind and behavior turned …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=wD90EAAAQBAJ&oi=fnd&pg=PA366&dq=commoncrawl&ots=cFuiqkafcD&sig=CqQx5Bv7dxtxoYrlkVD_Qp8nYdc"]}
+{"year":"2022","title":"PETCI: A Parallel English Translation Dataset of Chinese Idioms","authors":["K Tang - arXiv preprint arXiv:2202.09509, 2022"],"snippet":"… RoBERTa, for example, has part of its pre-training data from Reddit and CommonCrawl (Liu … Similarly, we expect the Wikipedia dataset to have a lower PoI than CommonCrawl. The … use the cased 300-dimensional GloVe vectors pre-trained on …","url":["https://arxiv.org/pdf/2202.09509"]}
+{"year":"2022","title":"Phishing Detection Using URL-based XAI Techniques","authors":["PRG Hernandes, CP Floret, KFC De Almeida… - 2021 IEEE Symposium …, 2021"],"snippet":"… As a result, 5,000 phishing web pages were selected based on URLs from PhishTank 1, OpenPhish 2, and another 5,000 legitimate pages based on URLs of Alexa 3 and the archive of CommonCrawl 4. Subsequently, this dataset was …","url":["https://ieeexplore.ieee.org/abstract/document/9659981/"]}
+{"year":"2022","title":"Phishing URL Detection: A novel hybrid Approach using Long Short-Term Memory and Gated Recurrent Units","authors":["BAS Dilhara - International Journal of Computer Applications"],"snippet":"Phishing is one of the oldest types of cyber-attack, which mostly comes in the form of camouflaged URLs to delude the users to disclose their personal information for malevolent purposes of the attacker. It is one of the easiest ways of inducing people …","url":["https://www.researchgate.net/profile/Shashie-Dilhara/publication/357269439_Phishing_URL_Detection_A_novel_hybrid_Approach_using_Long_Short-Term_Memory_and_Gated_Recurrent_Units/links/61c41df0abcb1b520ada4c9c/Phishing-URL-Detection-A-novel-hybrid-Approach-using-Long-Short-Term-Memory-and-Gated-Recurrent-Units.pdf"]}
+{"year":"2022","title":"Phishing URL Identification Using Machine Learning, Ensemble Learning and Deep Learning Techniques","authors":["K Laxmi Prasanna, KV Pradeepthi, A Saxena - Smart Intelligent Computing and …, 2022"],"snippet":"Demand for online applications and services is increasing day by day, whereas the security lapses in them is also becoming prominent. One of the major online threats, phishing, is consistently used to dupe users for retrieving sensitive information like …","url":["https://link.springer.com/chapter/10.1007/978-981-16-9705-0_56"]}
+{"year":"2022","title":"Phishing website detection: How effective are deep learning‐based models and hyperparameter optimization?","authors":["M Almousa, T Zhang, A Sarrafzadeh, M Anwar - Security and Privacy, 2022"],"snippet":"… The phishing webpages have been collected from PhishTank36 and OpenPhish,37 while the sources of legitimate webpages were Alexa38 and Common Crawl.The second dataset was obtained from Reference 40 that we refer to as Kumar-dataset …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/spy2.256"]}
+{"year":"2022","title":"Phonetic, Semantic, and Articulatory Features in Assamese-Bengali Cognate Detection","authors":["A Nath, R Ghosh, N Krishnaswamy"],"snippet":"In this paper, we propose a method to detect if words in two similar languages, Assamese and Bengali, are cognates. We mix phonetic, semantic, and articulatory features and use the cognate detection task to analyze the relative informational …","url":["https://www.nikhilkrishnaswamy.com/assets/docs/pdfs/VarDial-2022.pdf"]}
+{"year":"2022","title":"Phrase-Based Affordance Detection via Cyclic Bilateral Interaction","authors":["L Lu, W Zhai, H Luo, Y Kang, Y Cao - arXiv preprint arXiv:2202.12076, 2022"],"snippet":"… Meanwhile, for linguistic feature extraction, we first adopt the GloVe word embeddings [42] pre-trained on Common Crawl (840B tokens) to initialize the parameters of embedding layers then a LSTM is employed as the language feature …","url":["https://arxiv.org/pdf/2202.12076"]}
+{"year":"2022","title":"Plansformer: Generating Symbolic Plans using Transformers","authors":["V Pallagani, B Muppasani, K Murugesan, F Rossi… - arXiv preprint arXiv …, 2022"],"snippet":"… Large Language Models (LLM) such as BERT [16], RoBERTa [17], and GPT3 [3] are pre-trained on extensive unstructured knowledge from public data such as Wikipedia, Bookcorpus, and Commoncrawl, have shown impressive results in …","url":["https://arxiv.org/pdf/2212.08681"]}
+{"year":"2022","title":"PLAtE: A Large-scale Dataset for List Page Web Extraction","authors":["A San, J Bakus, C Lockard, D Ciemiewicz, Y Ji, S Atluri… - arXiv preprint arXiv …, 2022"],"snippet":"… We construct PLAtE by collecting list pages from Common Crawl, then annotating them on Mechanical Turk. Quantitative and qualitative analyses are performed to demonstrate PLAtE has high-quality annotations. We establish strong baseline …","url":["https://arxiv.org/pdf/2205.12386"]}
+{"year":"2022","title":"Political Event Coding as Text to Text Sequence Generation","authors":["Y Dai, BJ Radford, A Halterman"],"snippet":"We report on the current status of an effort to produce political event data from unstructured text via a Transformer language model. Compelled by the current lack of publicly available and up-to-date event coding software, we seek to train a model …","url":["https://yaoyaodai.github.io/files/CASE_2022.pdf"]}
+{"year":"2022","title":"Politics and Virality in the Time of Twitter: A Large-Scale Cross-Party Sentiment Analysis in Greece, Spain and United Kingdom","authors":["D Antypas, A Preece, JC Collados - arXiv preprint arXiv:2202.00396, 2022"],"snippet":"Social media has become extremely influential when it comes to policy making in modern societies especially in the western world (eg, 48% of Europeans use social media every day or almost every day). Platforms such as Twitter allow users to follow …","url":["https://arxiv.org/pdf/2202.00396"]}
+{"year":"2022","title":"Politics as Usual? Antecedents of Radical-Right Frames in US Electoral Discourse","authors":["B Bonikowski, Y Luo, O Stuhler - 2021"],"snippet":"… This extension of the original BERT model relies on the same general architecture but expands the training data to 63 million English news articles from CommonCrawl, 38 gigabytes of textual data from the OpenWebText corpus, and a 31-gigabyte …","url":["https://osf.io/preprints/socarxiv/uhvbp/download"]}
+{"year":"2022","title":"Politics as Usual? Measuring Populism, Nationalism, and Authoritarianism in US Presidential Campaigns (1952–2020) with Deep Neural Language Models","authors":["B Bonikowski, Y Luo, O Stuhler - Sociological Methods & Research, 2022"],"snippet":"… but expands the training data to 63 million English news articles from CommonCrawl, 38 gigabytes of textual data from the OpenWebText … corpus, and a 31-gigabyte subset of CommonCrawl data known as Stories. In addition, the …","url":["https://files.osf.io/v1/resources/uhvbp/providers/osfstorage/61eeccc0133169053a9928ce?action=download&direct&version=3"]}
+{"year":"2022","title":"POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection","authors":["Y Liu, XF Zhang, D Wegsman, N Beauchamp, L Wang - arXiv preprint arXiv …, 2022"],"snippet":"Ideology is at the core of political science research. Yet, there still does not exist general-purpose tools to characterize and predict ideology across different genres of text. To this end, we study Pretrained Language Models using novel ideology-driven …","url":["https://arxiv.org/pdf/2205.00619"]}
+{"year":"2022","title":"Post-hoc analysis of Arabic transformer models","authors":["A Abdelali, N Durrani, F Dalvi, H Sajjad - arXiv preprint arXiv:2210.09990, 2022"],"snippet":"Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While there have been an extrinsic evaluation …","url":["https://arxiv.org/pdf/2210.09990"]}
+{"year":"2022","title":"Poster: PhishLex: A Proactive Zero-Day Phishing Defence Mechanism using URL Lexical Features","authors":["M Fernando, AN Mahmood, MJM Chowdhury"],"snippet":"Google reports that 68% of all Phishing URLs that are blocked by them are zero-day phishing attacks that remain undetected using traditional blacklist-based approaches. Machine learning-based (ML) techniques can improve the accuracy of detecting zero-day …","url":["https://www.researchgate.net/profile/Matheesha-Fernando/publication/363698036_PhishLex_A_Proactive_Zero-Day_Phishing_Defence_Mechanism_using_URL_Lexical_Features/links/632a985f071ea12e364c4afa/PhishLex-A-Proactive-Zero-Day-Phishing-Defence-Mechanism-using-URL-Lexical-Features.pdf"]}
+{"year":"2022","title":"Posts on central websites need less originality to be noticed","authors":["M Coscia, C Vandeweerdt - Scientific Reports, 2022"],"snippet":"… We only kept domains that are also found in the Common Crawl data. This reduced the data to 3.8M posts. … We downloaded the domain graph from the Common Crawl for the November 2019–January 2020 period. Since from the Reddit …","url":["https://www.nature.com/articles/s41598-022-19433-9"]}
+{"year":"2022","title":"Pre-Trained Language Models and Their Applications","authors":["H Wang, J Li, H Wu, E Hovy, Y Sun - Engineering, 2022"],"snippet":"Pre-trained language models have achieved striking success in natural language processing (NLP), leading to a paradigm shift from supervised learning to pre-training followed by fine-tuning. The NLP community has witnessed a surge of research …","url":["https://www.sciencedirect.com/science/article/pii/S2095809922006324"]}
+{"year":"2022","title":"Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?","authors":["ESA Lee, S Thillainathan, S Nayak, S Ranathunga… - arXiv preprint arXiv …, 2022"],"snippet":"… mined one like from Common Crawl? Comparing mBART trained on Common Crawl versus domain-specific data, we see that for several … both in and not in mBART, 10k high-quality in-domain sentences leads to better performance than …","url":["https://arxiv.org/pdf/2203.08850"]}
+{"year":"2022","title":"Pre-trained transformers: an empirical comparison","authors":["S Casola, I Lauriola, A Lavelli - Machine Learning with Applications, 2022"],"snippet":"Pre-trained transformers have rapidly become very popular in the Natural Language Processing (NLP) community, surpassing the previous state of the art in a wide variety of tasks. While their effectiveness is indisputable, these methods are …","url":["https://www.sciencedirect.com/science/article/pii/S2666827022000445"]}
+{"year":"2022","title":"Pre-training large NLP-models by utilizing low-resource NLP-pipelines","authors":["Z van Cauter"],"snippet":"The dominating approach to Natural Language Processing problems is by pre-training models on large amounts of unsupervised text and fine-tuning them for use on downstream tasks. Over the years, this amount of unsupervised text has grown …","url":["https://pure.tue.nl/ws/portalfiles/portal/199766232/Cauter_Z.pdf"]}
+{"year":"2022","title":"Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection","authors":["L Di Liello, S Garg, L Soldaini, A Moschitti - arXiv preprint arXiv:2205.10455, 2022"],"snippet":"An important task for designing QA systems is answer sentence selection (AS2): selecting the sentence containing (or constituting) the answer to a question from a set of retrieved relevant documents. In this paper, we propose three novel sentence-level …","url":["https://arxiv.org/pdf/2205.10455"]}
+{"year":"2022","title":"Predicting Embedding Reliability in Low-Resource Settings Using Corpus Similarity Measures","authors":["J Dunn, H Li, D Sastre - arXiv preprint arXiv:2206.04330, 2022"],"snippet":"This paper simulates a low-resource setting across 17 languages in order to evaluate embedding similarity, stability, and reliability under different conditions. The goal is to use corpus similarity measures before training to predict properties of …","url":["https://arxiv.org/pdf/2206.04330"]}
+{"year":"2022","title":"Predicting Fine-Tuning Performance with Probing","authors":["Z Zhu, S Shahtalebi, F Rudzicz - Challenges {\\&, 2022"],"snippet":"… For example, after pre-training a deep neural model for 1000 steps on Wikipedia, is it more beneficial to continue training on Wikipedia or proceed to Common Crawl? The probing results could help answer questions of this kind, which we leave to …","url":["https://openreview.net/pdf?id=BLXlV3MBLZ5"]}
+{"year":"2022","title":"Preparing a Corpus and a Question Answering System for Slovene","authors":["M Zupanic, M Zirkelbach, U Šmajdek, M Jazbinšek"],"snippet":"Lack of proper training data is one of the key issues when developing natural language processing models based on less-resourced languages, such as Slovene. In this paper we discuss machine translation as a solution to this issue, with the …","url":["https://nl.ijs.si/jtdh22/pdf/JTDH2022_Zupancic-et-al_Preparing-a-Corpus-and-a-Question-Answering-System-for-Slovene.pdf"]}
+{"year":"2022","title":"Pretrained Language Models","authors":["J May"],"snippet":"… It was trained on 570gb of text (500b tokens) from common crawl, their previous data set, and some other ‘high quality’ data sets. When prompted with only a few examples (and sometimes with none at all) it outperformed SOTA on a wide variety …","url":["https://jonmay.github.io/USC-CS662/assets/files/pretrained.pdf"]}
+{"year":"2022","title":"Pretraining without Wordpieces: Learning Over a Vocabulary of Millions of Words","authors":["Z Feng, D Tang, C Zhou, J Liao, S Wu, X Feng, B Qin… - arXiv preprint arXiv …, 2022"],"snippet":"… Glove embedding is pretrained on Common Crawl dataset with 42B tokens 2 with 300 dimension. Given a sequence of words, we first get the corresponding 300-dimensional representation for each word through Glove Embedding. Then, we add a linear layer …","url":["https://arxiv.org/pdf/2202.12142"]}
+{"year":"2022","title":"Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy","authors":["D Ippolito, F Tramèr, M Nasr, C Zhang, M Jagielski… - arXiv preprint arXiv …, 2022"],"snippet":"Studying data memorization in neural language models helps us understand the risks (eg, to privacy or copyright) associated with models regurgitating training data, and aids in the evaluation of potential countermeasures. Many prior works -- and …","url":["https://arxiv.org/pdf/2210.17546"]}
+{"year":"2022","title":"Prior knowledge guided weakly supervised object detection and semantic segmentation","authors":["F Baltacı - 2022"],"snippet":"State-of-the-art recognition models in computer vision are trained using annotated training data. Collecting manual annotation for images is a time-consuming and tedious task. Annotation time and difficulty also change across computer vision tasks …","url":["https://open.metu.edu.tr/bitstream/handle/11511/96300/METU_Thesis_fatihbaltaci.pdf"]}
+{"year":"2022","title":"Privacy conflict analysis in web interaction models","authors":["P Inglis - 2022"],"snippet":"User privacy has become an important topic with strong implications for the manner by which software systems are designed and used. However, it is not a straightforward consideration on how the instrumentation of data processing …","url":["https://theses.gla.ac.uk/82875/1/2022inglisphd.pdf"]}
+{"year":"2022","title":"Privacy leakage analysis of text representations for Natural Language Processing","authors":["L CORÒ"],"snippet":"Natural language processing (NLP) offers powerful tools, such as text suggestions to help users be more efficient or classifiers that categorize documents by their content. These tools are usually powered by machine learning (ML) models that are trained …","url":["https://thesis.unipd.it/bitstream/20.500.12608/35514/1/Cor%C3%B2_Luca.pdf"]}
+{"year":"2022","title":"Privacy Policies of IoT Devices: Collection and Analysis","authors":["M Kuznetsov, E Novikova, I Kotenko, E Doynikova - Sensors, 2022"],"snippet":"Currently, personal data collection and processing are widely used while providing digital services within mobile sensing networks for their operation, personalization, and improvement. Personal data are any data that identifiably describe a person …","url":["https://www.mdpi.com/1424-8220/22/5/1838/pdf"]}
+{"year":"2022","title":"Proactive Interference-aware Resource Management in Deep Learning Training Cluster","authors":["GF Yeung - 2022"],"snippet":"Deep Learning (DL) applications are growing at an unprecedented rate across many domains, ranging from weather prediction, map navigation to medical imaging. However, training these deep learning models in large-scale compute clusters face …","url":["https://eprints.lancs.ac.uk/id/eprint/172142/1/2022yeungphd.pdf"]}
+{"year":"2022","title":"Probing for Dutch Relative Pronoun Choice","authors":["G Bouma - Computational Linguistics in the Netherlands Journal, 2021"],"snippet":"We propose a linguistically motivated version of the relative pronoun probing task for Dutch (where a model has to predict whether a masked token is either die or dat), collect realistic data for it using a parsed corpus, and probe the performance of four …","url":["https://www.clinjournal.org/index.php/clinj/article/download/121/105"]}
+{"year":"2022","title":"Probing language identity encoded in pre-trained multilingual models: a typological view","authors":["J Zheng, Y Liu - PeerJ Computer Science, 2022"],"snippet":"… It is trained on CommonCrawl corpora with 12 layers and 768 hidden states. The vocabulary size is 250k, The tool for tokenization is free, namely, the Sentence Piece (Kudo & Richardson, 2018). The only task is the dynamic mask language model. …","url":["https://peerj.com/articles/cs-899/"]}
+{"year":"2022","title":"Probing Pre-Trained Language Models for Cross-Cultural Differences in Values","authors":["A Arora, LA Kaffee, I Augenstein - arXiv preprint arXiv:2203.13722, 2022"],"snippet":"… 2019) and is trained with an MLM objective on 2.5 TB of filtered CommonCrawl corpus data in 100 languages. It shows strong multilingual performance across a range of benchmarks and is commonly used for extracting multilingual sentence encodings. …","url":["https://arxiv.org/pdf/2203.13722"]}
+{"year":"2022","title":"Proceedings of the 13th Conference on\" Data analysis methods for software systems","authors":["J Bernatavičienė - Vilnius University Proceedings, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://www.zurnalai.vu.lt/proceedings/article/download/29893/28890"]}
+{"year":"2022","title":"Project European Language Equality (ELE) Grant agreement no. LC-01641480–101018166 ELE Coordinator Prof. Dr. Andy Way (DCU) Co-coordinator Prof. Dr …","authors":["G Backfried, M Skowron, E Navas, A Bērziņš… - 2022"],"snippet":"D2. 14 provides an overview and describes the state of the art and developments within the field of Speech Technologies (ST). This field is interpreted to comprise technologies aimed at the processing and production of the human voice, both, from …","url":["https://european-language-equality.eu/wp-content/uploads/2022/03/ELE___Deliverable_D2_14__Speech__Technologies.pdf"]}
+{"year":"2022","title":"Prompt-GAN–Customisable hate speech and extremist datasets via radicalised neural language models","authors":["J Govers - 2022"],"snippet":"Online hate speech and violent extremism knows no borders, no political boundaries, no remorse. Researchers face an uphill battle to collect hate speech data in volumes and topical diversity suitable for training state-of-the art content-moderation systems …","url":["https://researchcommons.waikato.ac.nz/bitstream/handle/10289/15259/thesis.pdf?sequence=4&isAllowed=y"]}
+{"year":"2022","title":"Prompting ELECTRA: Few-Shot Learning with Discriminative Pre-Trained Models","authors":["M Xia, M Artetxe, J Du, D Chen, V Stoyanov - arXiv preprint arXiv:2205.15223, 2022"],"snippet":"Pre-trained masked language models successfully perform few-shot learning by formulating downstream tasks as text infilling. However, as a strong alternative in full-shot settings, discriminative pre-trained models like ELECTRA do not fit into the paradigm …","url":["https://arxiv.org/pdf/2205.15223"]}
+{"year":"2022","title":"Promt systems for wmt21 terminology translation task","authors":["A Molchanov, V Kovalenko, F Bykov - Proceedings of the Sixth Conference on …, 2021"],"snippet":"… We first build an English-Russian system using all parallel data (except commoncrawl which we believe to be of bad quality; basic filtering is applied) including the Edinborough corpus of Russian news translated into English and …","url":["https://aclanthology.org/2021.wmt-1.83.pdf"]}
+{"year":"2022","title":"Prospects for Dutch Emotion Detection: Insights from the new EmotioNL Dataset","authors":["L De Bruyne, O De Clercq, V Hoste - Computational Linguistics in the Netherlands …, 2021"],"snippet":"Although emotion detection has become a crucial research direction in NLP, the main focus is on English resources and data. The main obstacles for more specialized emotion detection are the lack of annotated data in smaller languages …","url":["https://clinjournal.org/index.php/clinj/article/download/138/144"]}
+{"year":"2022","title":"Protecting Systems From Exploits Using Language-Theoretic Security","authors":["P Anantharaman - 2022"],"snippet":"Any computer program processing input from the user or network must validate the input. Input-handling vulnerabilities occur in programs when the software component responsible for filtering malicious input---the parser---does not perform …","url":["https://digitalcommons.dartmouth.edu/cgi/viewcontent.cgi?article=1081&context=dissertations"]}
+{"year":"2022","title":"PsychBERT: A Mental Health Language Model for Social Media Mental Health Behavioral Analysis","authors":["V Vajre, M Naylor, U Kamath, A Shehu - 2021 IEEE International Conference on …, 2021"],"snippet":"Mental health behaviors are now recognized as primary factors contributing to suicide. This paper puts forth a novel mental health language model to address mental health and makes several contributions. First, it proposes a taxonomy and …","url":["https://ieeexplore.ieee.org/abstract/document/9669469/"]}
+{"year":"2022","title":"Punctuation Restoration in Spanish Customer Support Transcripts using Transfer Learning","authors":["X Zhu, S Gardiner, D Rossouw, T Roldán… - arXiv preprint arXiv …, 2022"],"snippet":"Automatic Speech Recognition (ASR) systems typically produce unpunctuated transcripts that have poor readability. In addition, building a punctuation restoration system is challenging for low-resource languages, especially for domain-specific …","url":["https://arxiv.org/pdf/2205.13961"]}
+{"year":"2022","title":"Qasar: Self-Supervised Learning Framework for Extractive Question Answering","authors":["H Assem, R Sarkar, S Dutta - 2021 IEEE International Conference on Big Data (Big …, 2021"],"snippet":"… Pretrained transformer based language models like BERT [8] are trained initially on large unlabelled data from common crawl corpus and Wikipedia dumps. With the creation of large labelled open-domain QA datasets like WikiQA [9], SQuAD [10] …","url":["https://ieeexplore.ieee.org/abstract/document/9671570/"]}
+{"year":"2022","title":"QianXun: A Novel Enterprise File Search Framework","authors":["C Si, P Qi, H Xue, Y Sun - 2022 IEEE 25th International Conference on Computer …, 2022"],"snippet":"… Subsequently, Google proposed mT5 [7], a multilingual variant of T5 that is pre-trained on a new Common Crawl-based dataset covering 101 languages, which offers the possibility of processing Chinese texts. Then, based on the mT5, Su Jianlin trained …","url":["https://ieeexplore.ieee.org/abstract/document/9776101/"]}
+{"year":"2022","title":"QMLEx: Data Driven Digital Transformation in Marketing Analytics","authors":["A Geronazzo, M Ziegler - 2021 IEEE International Conference on Big Data (Big …, 2021"],"snippet":"This paper presents a data driven approach to replace expert driven business processes. The QMLEx methodology combines NLP algorithms to improve data quality, ML techniques to perform the task and exploits external data sources to …","url":["https://ieeexplore.ieee.org/abstract/document/9671890/"]}
+{"year":"2022","title":"Qualitative Analysis of Text Summarization Techniques and Its Applications in Health Domain","authors":["D Yadav, N Lalit, R Kaushik, Y Singh, AK Yadav… - Computational Intelligence …, 2022"],"snippet":"For the better utilization of the enormous amount of data available to us on the Internet and in different archives, summarization is a valuable method. Manual summarization by experts is an almost impossible and time-consuming activity …","url":["https://www.hindawi.com/journals/cin/2022/3411881/"]}
+{"year":"2022","title":"Qualitative Measures for Ad hoc Table Retrieval","authors":["M Khodabakhsh, E Bagheri - Information Sciences, 2022"],"snippet":"The focus of our work is the ad hoc table retrieval task, which aims to rank a list of structured tabular objects in response to a user query. Given the importance of this task, various methods have already been proposed in the literature that focus on …","url":["https://www.sciencedirect.com/science/article/pii/S0020025522005126"]}
+{"year":"2022","title":"Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP","authors":["T Nguyen, G Ilharco, M Wortsman, S Oh, L Schmidt - arXiv preprint arXiv:2208.05516, 2022"],"snippet":"Web-crawled datasets have enabled remarkable generalization capabilities in recent image-text models such as CLIP (Contrastive Language-Image pre-training) or Flamingo, but little is known about the dataset creation processes. In this work, we …","url":["https://arxiv.org/pdf/2208.05516"]}
+{"year":"2022","title":"Quantifying Memorization Across Neural Language Models","authors":["N Carlini, D Ippolito, M Jagielski, K Lee, F Tramer… - arXiv preprint arXiv …, 2022"],"snippet":"… These models were trained on C4, a cleaned and filtered version of the English web pages from the Common Crawl, which totals 806 GB in size. At 11 billion parameters, the largest T5 model is the largest publicly available masked language …","url":["https://arxiv.org/pdf/2202.07646"]}
+{"year":"2022","title":"Quantifying the Polarity of Noun Phrases","authors":["BI Ersoy"],"snippet":"While sentiment analysis is a popular NLP subfield, not every area within gets the same amount of attention. For example, classifying the sentiment of texts seems to be quite in demand, however, rarely does it also include determining how positive or …","url":["https://www.cl.uzh.ch/dam/jcr:d3356468-e322-4a8a-befb-23f95590e497/BachelorThesis_BernaErsoy_2022.pdf"]}
+{"year":"2022","title":"Query Refinement Prompts for Closed-Book Long-Form Question Answering","authors":["RK Amplayo, K Webster, M Collins, D Das, S Narayan - arXiv preprint arXiv …, 2022"],"snippet":"Large language models (LLMs) have been shown to perform well in answering questions and in producing long-form texts, both in few-shot closed-book settings. While the former can be validated using well-known evaluation metrics, the latter is …","url":["https://arxiv.org/pdf/2210.17525"]}
+{"year":"2022","title":"Query-Driven Graph-Based User Recommender System","authors":["Y Li - 2022"],"snippet":"Current Social Networking Systems (SNS) such as YouTube are creator-driven systems in which creators create content and users search among available content to find what they want. However, queries from users can be time-sensitive, such as …","url":["https://ruor.uottawa.ca/bitstream/10393/43742/1/Li_Yansong_2022_thesis.pdf"]}
+{"year":"2022","title":"QueryForm: A Simple Zero-shot Form Entity Query Framework","authors":["Z Wang, Z Zhang, J Devlin, CY Lee, G Su, H Zhang… - arXiv preprint arXiv …, 2022"],"snippet":"Zero-shot transfer learning for document understanding is a crucial yet under-investigated scenario to help reduce the high cost involved in annotating document entities. We present a novel query-based framework, QueryForm, that extracts entity values from …","url":["https://arxiv.org/pdf/2211.07730"]}
+{"year":"2022","title":"Question Answering in Czech via Machine Translation and Cross-lingual Transfer","authors":["K Macková - 2022"],"snippet":"Reading comprehension and question answering are computer science disciplines in the field of natural language processing and information retrieval. Reading comprehension is the ability of the model to read text, process it and understand its …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/178197/150056797.pdf?sequence=1"]}
+{"year":"2022","title":"Question Generation and Answering in the Electrical Power System Components Domain","authors":["A Malik - 2022"],"snippet":"… This is English portion of Common Crawl data-set [Nag]. It has 63 M news articles crawled between … It is a subset of CommonCrawl data after filtering to match the story-like style of Winograd … To generate question corpus questions were …","url":["https://mediatum.ub.tum.de/doc/1690759/document.pdf"]}
+{"year":"2022","title":"Quick and (Maybe Not So) Easy Detection of Anorexia in Social Media","authors":["H Amini, E Mohammadi, L Kosseim - Early Detection of Mental Health Disorders by …, 2022"],"snippet":"This book chapter overviews our participation to the first sub-task of eRisk 2019 shared task, which was focused on the task of early detection of anorexia in Reddit posts. Our approach was to utilize several attention-based neural sub-models to …","url":["https://link.springer.com/chapter/10.1007/978-3-031-04431-1_6"]}
+{"year":"2022","title":"Quick and (Maybe Not So) Easy Detection of Anorexia in Social Media: To Explainability and Beyond","authors":["H Amini, E Mohammadi, L Kosseim - Early Detection of Mental Health Disorders by …, 2022"],"snippet":"This book chapter overviews our participation to the first sub-task of eRisk 2019 shared task, which was focused on the task of early detection of anorexia in Reddit posts. Our approach was to utilize several attention-based neural sub-models to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=03KJEAAAQBAJ&oi=fnd&pg=PA141&dq=commoncrawl&ots=ilEvY4CTlF&sig=PwxjLELSMl0YX7p_MJjbgn7ZghI"]}
+{"year":"2022","title":"RAPIDS cuGraph","authors":["A Fender, B Rees, J Eaton - Massive Graph Analytics"],"snippet":"… -scale PageRank computations using the Common Crawl dataset [5].The Common Crawl dataset captures link relationships between web … Our system delivered much faster performance for the Common Crawl dataset, but the largest …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003033707-22/rapids-cugraph-alex-fender-brad-rees-joe-eaton"]}
+{"year":"2022","title":"Readability of English, German, and Russian Disease-Related Wikipedia Pages: Automated Computational Analysis","authors":["J Gordejeva, R Zowalla, M Pobiruchin, M Wiesner - Journal of Medical Internet …, 2022"],"snippet":"Background Wikipedia is a popular encyclopedia for healthand disease-related information in which patients seek advice and guidance on the web. Yet, Wikipedia articles can be unsuitable as patient education materials, as investigated in previous …","url":["https://www.jmir.org/2022/5/e36835/"]}
+{"year":"2022","title":"Reading Comprehension","authors":["RS Roy, A Anand - Question Answering for the Curated Web, 2022"],"snippet":"… Corpora of curated text (like Wikipedia), large volumes of uncurated social-media posts, and massive Web document collection projects such as Common Crawl,1 are used to train these models. The key idea is that rather than going through the trouble …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-79512-1_9.pdf"]}
+{"year":"2022","title":"RECOGNITION THROUGH SPONTANEOUS SPEECH","authors":["S Luz, F Haider, D Fromm, B MacWhinney"],"snippet":"Alzheimer’s disease (AD) is a chronic neurodegenerative disease, without any known treatment. This disease progressively destroys brain structures, such as the hippocampus and entorhinal cortex, due to the accumulation of pathological forms of …","url":["https://www.research.ed.ac.uk/files/260484259/9782889718542_3.PDF"]}
+{"year":"2022","title":"Reducing Disambiguation Biases in NMT by Leveraging Explicit Word Sense Information","authors":["N Campolungo, T Pasini, D Emelin, R Navigli - … of the 2022 Conference of the North …, 2022"],"snippet":"Recent studies have shed some light on a common pitfall of Neural Machine Translation (NMT) models, stemming from their struggle to disambiguate polysemous words without lapsing into their most frequently occurring senses in the …","url":["https://aclanthology.org/2022.naacl-main.355.pdf"]}
+{"year":"2022","title":"Reducing Health Misinformation in Search Results","authors":["D Zhang - 2022"],"snippet":"… But topics in the 2020 track don’t have relevant documents in C4.en.noclean because it was extracted from the April 2019 snapshot3 of the Common Crawl corpus. Therefore, we performed our experiments on the data from the 2019 track …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18602/Zhang_Dake.pdf?sequence=3"]}
+{"year":"2022","title":"Reducing the labeling effort for entity resolution using distant supervision and active learning","authors":["A Primpeli - 2022"],"snippet":"… during the period 2012 to 2020 by extracting structured data from the Common Crawl web corpus.Along with this analysis, we are the first to … [C3] WDC Product Corpus We exploit semantically annotated productrelated data extracted from the …","url":["https://madoc.bib.uni-mannheim.de/62507/1/PhD_Thesis_Primpeli.pdf"]}
+{"year":"2022","title":"Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Model","authors":["XP Nguyen, S Joty, W Kui, AT Aw - arXiv preprint arXiv:2205.15544, 2022"],"snippet":"… For each group, we use monolingual corpora from the relevant languages of the Common Crawl dataset, which contains data from totally 25 languages [21]. We limit the amount of monolingual data per language to up to 100M sentences. Similarly to …","url":["https://arxiv.org/pdf/2205.15544"]}
+{"year":"2022","title":"Refining Word Embeddings with Sentiment Information for Sentiment Analysis","authors":["M Kasri, M Birjali, M Nabil, A Beni-Hssane, A El-Ansari… - Journal of ICT …, 2022"],"snippet":"Natural Language Processing problems generally require the use of pre-trained distributed word representations to be solved with deep learning models. However, distributed representations usually rely on contextual information which prevents …","url":["https://journals.riverpublishers.com/index.php/JICTS/article/download/13885/14687"]}
+{"year":"2022","title":"Register identification from the unrestricted open Web using the Corpus of Online Registers of English","authors":["V Laippala, S Rönnqvist, M Oinonen, AJ Kyröläinen… - Language Resources and …, 2022"],"snippet":"This article examines the automatic identification of Web registers, that is, text varieties such as news articles and reviews. Most studies have focused on corpora restricted to include only preselected classes with well-defined characteristics …","url":["https://link.springer.com/article/10.1007/s10579-022-09624-1"]}
+{"year":"2022","title":"Register variation remains stable across 60 languages","authors":["H Li, J Dunn, A Nini - Corpus Linguistics and Linguistic Theory, 2022"],"snippet":"This paper measures the stability of cross-linguistic register variation. A register is a variety of a language that is associated with extra-linguistic context. The relationship between a register and its context is functional: the linguistic features that make up a …","url":["https://arxiv.org/pdf/2209.09813"]}
+{"year":"2022","title":"Regressing Word and Sentence Embeddings for Low-Resource Neural Machine Translation","authors":["IJ Unanue, EZ Borzeshi, M Piccardi - IEEE Transactions on Artificial Intelligence, 2022"],"snippet":"… The training set contains over 5M sentence pairs collected from the Europarl, CommonCrawl and Newscommentary parallel corpora. As validation and test sets, we have used the newstest2017 and the newstest2018 datasets, respectively. This …","url":["https://ieeexplore.ieee.org/abstract/document/9813389/"]}
+{"year":"2022","title":"Regularization-based Pruning of Irrelevant Weights in Deep Neural Architectures","authors":["B Giovanni, R Matteo, C Rossella - APPLIED INTELLIGENCE, 2022","G Bonetta, M Ribero, R Cancelliere - arXiv preprint arXiv:2204.04977, 2022"],"snippet":"Deep neural networks exploiting millions of parameters are nowadays the norm in deep learning applications. This is a potential issue because of the great amount of computational resources needed for training, and of the possible loss of …","url":["https://arxiv.org/pdf/2204.04977","https://iris.unito.it/bitstream/2318/1877432/1/Sparsity_Applied_Intelligence_Final.pdf"]}
+{"year":"2022","title":"Related Questions Retrieval Model in Stack Overflow based on Semantic Matching","authors":["Z Qin, Y Wu, J Pei, J Lu, S Huang, L Liu - … IEEE 46th Annual Computers, Software, and …, 2022"],"snippet":"… The GloVe-840B [23] is pre-trained on the Common Crawl corpus with many texts that are irrelevant to the software engineering domain. The SE (15G) [9] is pre-trained on a 15GB corpus collected from Stack Overflow data dumps. …","url":["https://ieeexplore.ieee.org/abstract/document/9842482/"]}
+{"year":"2022","title":"Relational Embeddings for Language Independent Stance Detection","authors":["JF de Landa, R Agerri - arXiv preprint arXiv:2210.05715, 2022"],"snippet":"The large majority of the research performed on stance detection has been focused on developing more or less sophisticated text classification systems, even when many benchmarks are based on social network data such as Twitter. This paper …","url":["https://arxiv.org/pdf/2210.05715"]}
+{"year":"2022","title":"Report 2 on ASR Systems","authors":["TNN KIT, CH KIT - 2022"],"snippet":"1 Executive Summary In this deliverable we describe the final automatic speech recognition (ASR) systems that we created for the ELITR speech translation system. In Section 2 we describe our work. In the subsections 2.1 and 2.2 we address tasks …","url":["https://elitr.eu/wp-content/uploads/2022/06/D2.2.pdf"]}
+{"year":"2022","title":"Representations of emotion concepts: Comparison across pairwise, appraisal feature-based, and word embedding-based similarity spaces","authors":["M Kwon, T Wager, J Phillips - Proceedings of the Annual Meeting of the Cognitive …, 2022"],"snippet":"A question that has long interested cognitive scientists is how to best represent the different emotions we experience and attribute to others. For example, constructionist and appraisal theories propose that differences between emotions …","url":["https://escholarship.org/content/qt8vj3d366/qt8vj3d366.pdf"]}
+{"year":"2022","title":"Reproducible scaling laws for contrastive language-image learning","authors":["M Cherti, R Beaumont, R Wightman, M Wortsman… - arXiv preprint arXiv …, 2022"],"snippet":"… More recently, larger image-text datasets have been collected from Common Crawl [1]. The resulting datasets, LAION-400M [66] and … Both LAION-400M [66] and LAION-5B [65] are open, public image-text datasets that were composed by …","url":["https://arxiv.org/pdf/2212.07143"]}
+{"year":"2022","title":"Reproduction and Replication of an Adversarial Stylometry Experiment","authors":["H Wang, P Juola, A Riddell - arXiv preprint arXiv:2208.07395, 2022"],"snippet":"Maintaining anonymity while communicating using natural language remains a challenge. Standard authorship attribution techniques that analyze candidate authors' writing styles achieve uncomfortably high accuracy even when the number …","url":["https://arxiv.org/pdf/2208.07395"]}
+{"year":"2022","title":"Research Article COVID-19 Outbreak Forecasting Based on Vaccine Rates and Tweets Classification","authors":["Y Didi, A Walha, MB Halima, A Wali - 2022"],"snippet":"Copyright© 2022 Y. Didi et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e …","url":["https://downloads.hindawi.com/journals/cin/2022/4535541.pdf"]}
+{"year":"2022","title":"Research Article Qualitative Analysis of Text Summarization Techniques and Its Applications in Health Domain","authors":["AK Yadav, KV Bhadane, A Kumar, B Khan - 2022"],"snippet":"Summarizing textual information requires understanding and analyzing the linguistic, conceptual, and semantic attributes of the given information. In addition, a summary generated should succeed in incorporating the essential details and the main ideas …","url":["https://www.academia.edu/download/83013544/3411881.pdf"]}
+{"year":"2022","title":"Research Background","authors":["R Richner - Auto-Grader-Auto-Grading Free Text Answers, 2022"],"snippet":"Research Background Page 1 3 Research Background Firstly, this chapter will introduce the technological background needed to understand how a state-of-the-art auto-grader may look and secondly elaborate on related work in the field of …","url":["https://link.springer.com/content/pdf/10.1007/978-3-658-39203-1_3.pdf"]}
+{"year":"2022","title":"Rethinking Data Governance: A Labor-Oriented Approach","authors":["H LI, N VINCENT - 2022"],"snippet":"… Prominent examples include Flickr photos [12], Wikipedia articles [14], and the Common Crawl dataset consisting of publicly available webpages [11]. In many of such cases, users produce data without being aware of its value and potential …","url":["https://criticalautomation.org/wp-content/uploads/2022/03/li-vincent-data-governance.pdf"]}
+{"year":"2022","title":"Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?","authors":["S Min, X Lyu, A Holtzman, M Artetxe, M Lewis… - arXiv preprint arXiv …, 2022","WMICL Work"],"snippet":"Large language models (LMs) are able to in-context learn--perform a new task via inference alone by conditioning on a few input-label pairs (demonstrations) and making predictions for new inputs. However, there has been little understanding of …","url":["https://arxiv.org/pdf/2202.12837","https://openreview.net/pdf?id=cnRGMv-Ak7u"]}
+{"year":"2022","title":"Revisiting CCNet for Quality Measurements in Galician","authors":["JE Ortega, I de-Dios-Flores, JR Pichel, P Gamallo - International Conference on …, 2022","JR Pichel, P Gamallo","P Gamallo - … Processing of the Portuguese Language: 15th …"],"snippet":"… In this article, we present our findings on reproducing the introduction of the common crawl corpus by Facebook, known as the CCNet … as the Common Crawl 2 corpus based on a “snapshot” of the web at a given time – the work on CCNet is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Df9kEAAAQBAJ&oi=fnd&pg=PA407&dq=commoncrawl&ots=UGnguc7I3u&sig=8yrKGw8bPU5TtHaLaA-1I63OUas","https://gramatica.usc.es/~gamallo/artigos-web/PROPOR2022.pdf","https://link.springer.com/chapter/10.1007/978-3-030-98305-5_38"]}
+{"year":"2022","title":"Revisiting DocRED--Addressing the Overlooked False Negative Problem in Relation Extraction","authors":["Q Tan, L Xu, L Bing, HT Ng - arXiv preprint arXiv:2205.12696, 2022"],"snippet":"The DocRED dataset is one of the most popular and widely used benchmarks for document-level relation extraction (RE). It adopts a recommend-revise annotation scheme so as to have a large-scale annotated dataset. However, we find that the …","url":["https://arxiv.org/pdf/2205.12696"]}
+{"year":"2022","title":"Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding","authors":["A Ghaddar, Y Wu, S Bagga, A Rashid, K Bibi… - arXiv preprint arXiv …, 2022"],"snippet":"… We collect pre-training data from the following sources: common crawl (CC), news (NEWS, ELKHAIR), and Wikipedia (WIKI).Recent … Common Crawl (CC): We used 10 shards of Common Crawl8 data from March to December 2020. After …","url":["https://arxiv.org/pdf/2205.10687"]}
+{"year":"2022","title":"RigoBERTa: A State-of-the-Art Language Model For Spanish","authors":["AV Serrano, GG Subies, HM Zamorano, NA Garcia… - arXiv preprint arXiv …, 2022"],"snippet":"… OSCAR [28] [29] is a very large multilingual corpus, obtained by language classification and filtering of the CommonCrawl7. It has a portion of … For example, javascript code, automatic writings, poor automatic translations or malformed …","url":["https://arxiv.org/pdf/2205.10233"]}
+{"year":"2022","title":"RobBERT-2022: Updating a Dutch Language Model to Account for Evolving Language Use","authors":["P Delobelle, T Winters, B Berendt - arXiv preprint arXiv:2211.08192, 2022"],"snippet":"… 2019) is based on automatically language-classified Common Crawl documents.The corpus has a release with data up until January 2022, which in contrast with previous releases is now a full documents corpus instead of the previous pre-shuffled …","url":["https://arxiv.org/pdf/2211.08192"]}
+{"year":"2022","title":"Robust Domain Adaptation for Pre-trained Multilingual Neural Machine Translation Models","authors":["M Grosso, P Ratnamogan, A Mathey, W Vanhuffel… - arXiv preprint arXiv …, 2022"],"snippet":"Recent literature has demonstrated the potential of multilingual Neural Machine Translation (mNMT) models. However, the most efficient models are not well suited to specialized industries. In these cases, internal data is scarce and expensive to …","url":["https://arxiv.org/pdf/2210.14979"]}
+{"year":"2022","title":"Robust Knowledge Acquisition in Answering Information-seeking Questions At Scale","authors":["E Kamalloo - 2022"],"snippet":"Answering information-seeking question involves retrieving relevant documents from a massive haystack of unstructured text corpora. This dissertation aims at building question answering (QA) systems that can be deployed in the wild where …","url":["https://era.library.ualberta.ca/items/7c56859b-ba57-40fc-8af3-6a6ab168e1e5/download/60cf2b19-0dbb-4340-a6e2-33fc1964ffd7"]}
+{"year":"2022","title":"Robust Phishing Detection Against Adversaries","authors":["S Al-Ahmadi - Journal: WSEAS TRANSACTIONS ON COMPUTER …, 2022"],"snippet":"Phishing websites have grown more recently than ever, and they become more intelligent, even against well-designed phishing detection techniques. Formerly, we have proposed in the literature a state-of-the-art URL-exclusive phishing detection …","url":["https://ouci.dntb.gov.ua/en/works/lRjbXjjl/"]}
+{"year":"2022","title":"Robustness Analysis of Grover for Machine-Generated News Detection","authors":["R Gagiano, MMH Kim, X Zhang, J Biggs"],"snippet":"Advancements in Natural Language Generation have raised concerns on its potential misuse for deep fake news. Grover is a model for both generation and detection of neural fake news. While its performance on automatically discriminating …","url":["https://alta2021.alta.asn.au/files/ALTW_2021_paper_7.pdf"]}
+{"year":"2022","title":"Romantic-Computing","authors":["E Horishny - arXiv preprint arXiv:2206.11864, 2022"],"snippet":"In this paper we compare various text generation models' ability to write poetry in the style of early English Romanticism. These models include: Character-Level Recurrent Neural Networks with Long Short-Term Memory, Hugging Face's GPT-2 …","url":["https://arxiv.org/pdf/2206.11864"]}
+{"year":"2022","title":"Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipedia","authors":["P Fedorov, A Mironov, G Chernishev - arXiv preprint arXiv:2210.06353, 2022"],"snippet":"… Therefore, relying on the Common Crawl dataset would require a multimachine environment. For example, in case of the WDC Web Table Corpus, the … Therefore, it is prohibitevely expensive for low-budged projects or individual students to use the …","url":["https://arxiv.org/pdf/2210.06353"]}
+{"year":"2022","title":"SALTED: A Framework for SAlient Long-Tail Translation Error Detection","authors":["V Raunak, M Post, A Menezes - arXiv preprint arXiv:2205.09988, 2022"],"snippet":"Traditional machine translation (MT) metrics provide an average measure of translation quality that is insensitive to the long tail of behavioral problems in MT. Examples include translation of numbers, physical units, dropped content and …","url":["https://arxiv.org/pdf/2205.09988"]}
+{"year":"2022","title":"Sample, Translate, Recombine: Leveraging Audio Alignments for Data Augmentation in End-to-end Speech Translation","authors":["TK Lam, S Schamoni, S Riezler - arXiv preprint arXiv:2203.08757, 2022"],"snippet":"End-to-end speech translation relies on data that pair source-language speech inputs with corresponding translations into a target language. Such data are notoriously scarce, making synthetic data augmentation by back-translation or …","url":["https://arxiv.org/pdf/2203.08757"]}
+{"year":"2022","title":"Samsung R&D Institute participation in WMT 2022 General MT Task","authors":["A Dobrowolski, M Klimaszewski, A Mysliwy…"],"snippet":"… CommonCrawl, we used only lines/paragraphs containing three or more sentences, which we split into single sentences. News-CommonCrawl … crawl and 100k sentences from CommonCrawl. Using this model, we selected sentences classified …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.17.pdf"]}
+{"year":"2022","title":"Sarcasm Detection Framework Using Emotion and Sentiment Features","authors":["O Vitman, Y Kostiuk, G Sidorov, A Gelbukh - arXiv preprint arXiv:2211.13014, 2022"],"snippet":"… We used Glove Common Crawl4 pretrained vectors (42 billion words version). For words with no pre-trained vectors, we checked their stemmed versions. If no pre-trained embedding were found, random vector was initialized. …","url":["https://arxiv.org/pdf/2211.13014"]}
+{"year":"2022","title":"Sarcasm detection using deep learning and ensemble learning","authors":["P Goel, R Jain, A Nayyar, S Singhal, M Srivastava - Multimedia Tools and …, 2022"],"snippet":"Across the globe, there is a noticeable upward trend of incorporating sarcasm in everyday life. This trend can be easily attributed to the frequent use of sarcasm in everyday life, but more specifically to social media and the Internet. This study aims …","url":["https://link.springer.com/article/10.1007/s11042-022-12930-z"]}
+{"year":"2022","title":"Scaling Laws and Interpretability of Learning from Repeated Data","authors":["D Hernandez, T Brown, T Conerly, N DasSarma… - arXiv preprint arXiv …, 2022"],"snippet":"Recent large language models have been trained on vast datasets, but also often on repeated data, either intentionally for the purpose of upweighting higher quality data, or unintentionally because data deduplication is not perfect and the model is …","url":["https://arxiv.org/pdf/2205.10487"]}
+{"year":"2022","title":"Scaling Laws Beyond Backpropagation","authors":["MJ Filipovich, A Cappelli, D Hesslow, J Launay - arXiv preprint arXiv:2210.14593, 2022"],"snippet":"… The models are trained on 30B tokens of English CommonCrawl data filtered with CCNet [41], with hyper-parameters adapted from GPT-3 [29], but with a context size of 512 for increased training speed. We chose different optimization hyper-parameters …","url":["https://arxiv.org/pdf/2210.14593"]}
+{"year":"2022","title":"SDW-ASL: A Dynamic System to Generate Large Scale Dataset for Continuous American Sign Language","authors":["Y Jiang - arXiv preprint arXiv:2210.06791, 2022"],"snippet":"… For example, the GPT-3 model with 175 billion parameters was trained using the ever-growing Common Crawl dataset with close to 1 trillion words. The largest dataset for ASL is dwarfed in comparison — so far it is only around 10-thousand …","url":["https://arxiv.org/pdf/2210.06791"]}
+{"year":"2022","title":"Second place solution of Amazon KDD Cup 2022: ESCI Challenge for Improving Product Search","authors":["X Qin, N Liang, H Zhang, W Zou, W Zhang"],"snippet":"How to improve the search experience is a hot topic that has been studied for decades in both academia and industry. KDD Cup 2022 ESCI Challenge organized by Amazon provides a large dataset with four categories of ESCI to improve …","url":["https://amazonkddcup.github.io/papers/8408.pdf"]}
+{"year":"2022","title":"Securing the Next Generation Web","authors":["B Eriksson - 2022"],"snippet":"… We evaluate Black Ostrich on a set of 8 821 unique validation patterns gathered from over 21 667 978 forms from a combination of the July 2021 Common Crawl and Tranco top 100K. For these forms and reconstructions of input elements …","url":["https://search.proquest.com/openview/086d85c81a8dd4762211543c916a6235/1.pdf?pq-origsite=gscholar&cbl=2026366&diss=y"]}
+{"year":"2022","title":"Security and Privacy Challenges for Intelligent Internet of Things Devices 2022 TADW: Traceable and Antidetection Dynamic Watermarking of Deep Neural Networks","authors":["J Dong, H Wang, Z He, J Niu, X Zhu, G Wu - Security and Communication Networks, 2022"],"snippet":"Deep neural networks (DNN) with incomparably advanced performance have been extensively applied in diverse fields (eg, image recognition, natural language processing, and speech recognition). Training a high-performance DNN model …","url":["https://www.hindawi.com/journals/scn/2022/9505808/"]}
+{"year":"2022","title":"Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge","authors":["D Merkx, SL Frank, M Ernestus - arXiv preprint arXiv:2202.10292, 2022"],"snippet":"Distributional semantic models capture word-level meaning that is useful in many natural language processing tasks and have even been shown to capture cognitive aspects of word meaning. The majority of these models are purely text based, even …","url":["https://arxiv.org/pdf/2202.10292"]}
+{"year":"2022","title":"SEHC: A Benchmark Setup to Identify Online Hate Speech in English","authors":["S Ghosh, A Ekbal, P Bhattacharyya, T Saha, A Kumar… - IEEE Transactions on …, 2022"],"snippet":"… The embeddings are fetched from GloVe (300-dimension) pre-trained word embedding, which was trained on the Common Crawl corpus (840 billion tokens). We pad input arrays with zeros to make input sequences the same length. On our …","url":["https://ieeexplore.ieee.org/abstract/document/9738838/"]}
+{"year":"2022","title":"Self-admitted technical debt classification using natural language processing word embeddings","authors":["AF Sabbah, AA Hanani - International Journal of Electrical and Computer …, 2023"],"snippet":"Recent studies show that it is possible to detect technical dept automatically from source code comments intentionally created by developers, a phenomenon known as self-admitted technical debt. This study proposes a system by which a comment …","url":["https://www.researchgate.net/profile/Ahmed-Sabbah/publication/366204787_Self-admitted_technical_debt_classification_using_natural_language_processing_word_embeddings/links/63977b01e42faa7e75b9f25c/Self-admitted-technical-debt-classification-using-natural-language-processing-word-embeddings.pdf"]}
+{"year":"2022","title":"SEMANTIC ACCOUNTS OF RISK PERCEPTION","authors":["Z Hussaina, R Mataa, DU Wulffa - life"],"snippet":"… Common Crawl, 1011 tokens …","url":["https://psychologie.unibas.ch/fileadmin/user_upload/psychologie/Beacon/SAoRP_Poster_Final.pdf"]}
+{"year":"2022","title":"Semantic Annotation of Numerical Data in Web Tables","authors":["Y Su - 2021"],"snippet":"A large portion of quantitative information about entities mentioned in Web pages is expressed as Web tables, and these tables often lack proper schema and annotation, which introduces challenges for the purpose of querying and further analysis. In this …","url":["https://scholar.archive.org/work/bb4fkx7uzzbi7pnelydtz4nnsy/access/wayback/https://era.library.ualberta.ca/items/b25fe525-b33c-4954-a5d4-3066f797cd34/view/a1788204-c1a8-4a67-be55-57005a93cabc/Su_Yuchen_202109_MSc.pdf"]}
+{"year":"2022","title":"Semantic Comparisons for Natural Language Processing Applications","authors":["L Lin - 2021"],"snippet":"For social scientists and other data practitioners, the abundance of available digital text data is a rich potential source for understanding social phenomena. As a result, practitioners have increasingly used text analysis methods on relevant corpora to …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48232/Lin_washington_0250E_23655.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"Semantic Cross Attention for Few-shot Learning","authors":["B Xiao, CL Liu, WH Hsaio - arXiv preprint arXiv:2210.06311, 2022"],"snippet":"Few-shot learning (FSL) has attracted considerable attention recently. Among existing approaches, the metric-based method aims to train an embedding network that can make similar samples close while dissimilar samples as far as possible and …","url":["https://arxiv.org/pdf/2210.06311"]}
+{"year":"2022","title":"Semantic Network: A Brief Review of its Datasets","authors":["M Trovati, S Awan - International Conference on Intelligent Networking and …, 2022"],"snippet":"Semantic networks are graphical representations, in terms of nodes and edges, of words and phrases from the linguistics vocabulary to form a meaning and relation between them to describe the intended target or object. It is part of the computer …","url":["https://link.springer.com/chapter/10.1007/978-3-031-14627-5_21"]}
+{"year":"2022","title":"Semantic projection recovers rich human knowledge of multiple object features from word embeddings","authors":["G Grand, IA Blank, F Pereira, E Fedorenko - Nature Human Behaviour, 2022"],"snippet":"How is knowledge about word meaning represented in the mental lexicon? Current computational models infer word meanings from lexical co-occurrence patterns. They learn to represent words as vectors in a multidimensional space, wherein …","url":["https://www.nature.com/articles/s41562-022-01316-8"]}
+{"year":"2022","title":"Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning","authors":["G Fan, J Wang, Y Li, D Zhang, R Miller - arXiv preprint arXiv:2210.01922, 2022"],"snippet":"Dataset discovery from data lakes is essential in many real application scenarios. In this paper, we propose Starmie, an end-to-end framework for dataset discovery from data lakes (with table union search as the main use case). Our proposed framework …","url":["https://web7.arxiv.org/pdf/2210.01922"]}
+{"year":"2022","title":"Semantics-driven Attentive Few-shot Learning over Clean and Noisy Samples","authors":["OB Baran, RG Cinbiş - arXiv preprint arXiv:2201.03043, 2022"],"snippet":"Over the last couple of years few-shot learning (FSL) has attracted great attention towards minimizing the dependency on labeled training examples. An inherent difficulty in FSL is the handling of ambiguities resulting from having too few training …","url":["https://arxiv.org/pdf/2201.03043"]}
+{"year":"2022","title":"SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding","authors":["HT Madabushi, E Gow-Smith, M Garcia, C Scarton… - arXiv preprint arXiv …, 2022"],"snippet":"This paper presents the shared task on Multilingual Idiomaticity Detection and Sentence Embedding, which consists of two subtasks: (a) a binary classification one aimed at identifying whether a sentence contains an idiomatic expression, and (b) a …","url":["https://arxiv.org/pdf/2204.10050"]}
+{"year":"2022","title":"Semi-Supervised Lifelong Language Learning","authors":["Y Zhao, Y Zheng, B Yu, Z Tian, D Lee, J Sun, H Yu, Y Li… - arXiv preprint arXiv …, 2022"],"snippet":"Lifelong learning aims to accumulate knowledge and alleviate catastrophic forgetting when learning tasks sequentially. However, existing lifelong language learning methods only focus on the supervised learning setting. Unlabeled data …","url":["https://arxiv.org/pdf/2211.13050"]}
+{"year":"2022","title":"Sentence Simplification Capabilities of Transfer-Based Models","authors":["S Štajner, KC Sheang, H Saggion - 2022"],"snippet":"… T5 is trained on Colossal Clean Crawled Corpus (C4), a dataset created by applying a set of filters to English-language text sourced from the public Common Crawl web scrape. • mT5 (Xue et al. 2021): a multilingual model based on T5 (Raffel …","url":["https://www.aaai.org/AAAI22Papers/AISI-7740.StajnerS.pdf"]}
+{"year":"2022","title":"SEntFiN 1.0: Entity‐aware sentiment analysis for financial news","authors":["A Sinha, S Kedas, R Kumar, P Malo - Journal of the Association for Information Science and …"],"snippet":"Fine‐grained financial sentiment analysis on news headlines is a challenging task requiring human‐annotated datasets to achieve high performance. Limited studies have tried to address the sentiment extraction task in a setting where multiple …","url":["https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24634"]}
+{"year":"2022","title":"Sentiment Analysis of COVID-19 Vaccination Responses From Twitter Using Ensemble Learning","authors":["Q Ismail, R Obeidat, K Alissa, E Al-Sobh - 2022 13th International Conference on …, 2022"],"snippet":"… As an alternative to BERT, we also use RoBERTa, a robust pre-trained language model for English, learned from 160GB of texts covering books, Wikipedia, CommonCrawl news, CommonCrawl stories, and web text contents [11]. Our SA …","url":["https://ieeexplore.ieee.org/abstract/document/9811132/"]}
+{"year":"2022","title":"Sentiment Analysis of Russian Reviews to Estimate the Usefulness of Drugs Using the Domain-Specific XLM-RoBERTa Model","authors":["A Sboev, A Naumov, I Moloshnikov, R Rybka - Biologically Inspired Cognitive …, 2022"],"snippet":"This paper considers the problem of classifying Russian-language drug reviews into five classes (corresponding to the authors’ rating scores) and into two classes (the drug is helpful or useless) in terms of the sentiment analysis task. The dataset of …","url":["https://link.springer.com/chapter/10.1007/978-3-030-96993-6_49"]}
+{"year":"2022","title":"Sentiment Analysis with Linguistic Knowledge","authors":["P KLIMEŠOVÁ"],"snippet":"… This thesis employs FastText CBOW word and text vectors with dimensionality 300 pre-trained on Wikipedia and the Common Crawl1 web corpus with negative sampling and n-gram length 52. The SVM, Logistic Regression, and Naïve Bayes …","url":["https://is.muni.cz/th/n0lnb/Sentiment_Analysis_cz.pdf"]}
+{"year":"2022","title":"Sentiment Analysis: A comparative study of Deep Learning and Machine Learning","authors":["R Manshani, T Thatte, K Suryawanshi - 2022"],"snippet":"… using the word vectors trained on Common Crawl and one hot encoding our y variable or training set. Our model contains a commencing layer of LSTM that will collect all the word embeddings corresponding to each token as an input. Our main …","url":["https://www.academia.edu/download/93879140/IRJET_V9I1121.pdf"]}
+{"year":"2022","title":"SentSpace: Large-Scale Benchmarking and Evaluation of Text using Cognitively Motivated Lexical, Syntactic, and Semantic Features","authors":["G Tuckute, A Sathe, M Wang, H Yoder, C Shain… - Proceedings of the 2022 …, 2022"],"snippet":"SentSpace is a modular framework for streamlined evaluation of text. SentSpacecharacterizes textual input using diverse lexical, syntactic, and semantic features derivedfrom corpora and psycholinguistic experiments. Core sentence …","url":["https://aclanthology.org/2022.naacl-demo.11.pdf"]}
+{"year":"2022","title":"Sequence Labeling Architectures in Diglossia","authors":["M Weidlich"],"snippet":"… FastText is a lightweight library pretrained on the Common Crawl dataset18 and Wikipedia in 157 languages including Arabic19 “using [Continuous Bag of Words] with position-weights, in 300 dimensions, with character n-grams of length 5, a …","url":["https://www.researchgate.net/profile/Mohamed-Megahed-2/publication/358956953_Sequence_Labeling_Architectures_in_Diglossia_-_a_case_study_of_Arabic_and_its_dialects/links/621f2684ef04e66eb74d6e08/Sequence-Labeling-Architectures-in-Diglossia-a-case-study-of-Arabic-and-its-dialects.pdf"]}
+{"year":"2022","title":"SEScore2: Retrieval Augmented Pretraining for Text Generation Evaluation","authors":["W Xu, X Qian, M Wang, L Li, WY Wang - arXiv preprint arXiv:2212.09305, 2022"],"snippet":"Is it possible to leverage large scale raw and raw parallel corpora to build a general learned metric? Existing learned metrics have gaps to human judgements, are model-dependent or are limited to the domains or tasks where human ratings are available. In this …","url":["https://arxiv.org/pdf/2212.09305"]}
+{"year":"2022","title":"SEUPD@ CLEF: Team Hextech on argument retrieval for comparative questions. the importance of adjectives in documents quality evaluation","authors":["A Chimetto, D Peressoni, E Sabbatini, G Tommasin… - Working Notes Papers of the …, 2022"],"snippet":"This report explains our approach to solve the Task 2 challenge about Argument Retrieval for Comparative Questions proposed by the third Touché lab on argument retrieval at CLEF 2022. Given a comparative topic, the task is to retrieve relevant …","url":["http://ceur-ws.org/Vol-3180/paper-256.pdf"]}
+{"year":"2022","title":"SexWEs: Domain-Aware Word Embeddings via Cross-lingual Semantic Specialisation for Chinese Sexism Detection in Social Media","authors":["A Jiang, A Zubiaga - arXiv preprint arXiv:2211.08447, 2022"],"snippet":"The goal of sexism detection is to mitigate negative online content targeting certain gender groups of people. However, the limited availability of labeled sexism-related datasets makes it problematic to identify online sexism for low-resource languages …","url":["https://arxiv.org/pdf/2211.08447"]}
+{"year":"2022","title":"Shedding Light on the Dark Web: Authorship Attribution in Radical Forums","authors":["L Ranaldi, F Ranaldi, F Fallucchi, FM Zanzotto - Information, 2022"],"snippet":"Online users tend to hide their real identities by adopting different names on the Internet. On Facebook or LinkedIn, for example, people usually appear with their real names. On other standard websites, such as forums, people often use …","url":["https://www.mdpi.com/2078-2489/13/9/435/pdf?version=1663167115"]}
+{"year":"2022","title":"Simple measures of bridging lexical divergence help unsupervised neural machine translation for low-resource languages","authors":["J Khatri, R Murthy, T Banerjee, P Bhattacharyya - Machine Translation, 2022"],"snippet":"… We consider CommonCrawl and the BigEst Estonian Corpus from the WMT18 shared task (Bojar et al. ) to create the monolingual corpus for Estonian. For English, we consider News Crawl 2017 and News Discussions 2017 from the WMT17 shared …","url":["https://link.springer.com/article/10.1007/s10590-021-09292-y"]}
+{"year":"2022","title":"Simultaneous Translation for Unsegmented Input: A Sliding Window Approach","authors":["S Sen, O Bojar, B Haddow - arXiv preprint arXiv:2210.09754, 2022"],"snippet":"In the cascaded approach to spoken language translation (SLT), the ASR output is typically punctuated and segmented into sentences before being passed to MT, since the latter is typically trained on written text. However, erroneous segmentation …","url":["https://arxiv.org/pdf/2210.09754"]}
+{"year":"2022","title":"SketchNE: Embedding Billion-Scale Networks Accurately in One Hour","authors":["Y Xie, Y Dong, J Qiu, W Yu, X Feng, J Tang"],"snippet":"We study large-scale network embedding with the goal of generating high-quality embeddings for networks with more than 1 billion vertices and 100 billion edges. Recent attempts LightNE and NetSMF propose to sparsify and factorize the (dense) …","url":["https://keg.cs.tsinghua.edu.cn/yuxiao/papers/2022.02-Xie-et-al-SketchNE.pdf"]}
+{"year":"2022","title":"Sliced at SemEval-2022 Task 11: Bigger, Better? Massively Multilingual LMs for Multilingual Complex NER on an Academic GPU Budget","authors":["B Plank - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"Massively multilingual language models (MMLMs) have become a widely-used representation method, and multiple large MMLMs were proposed in recent years. A trend is to train MMLMs on larger text corpora or with more layers. In this paper we …","url":["https://aclanthology.org/2022.semeval-1.205.pdf"]}
+{"year":"2022","title":"SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing","authors":["C He, S Zheng, A Zhang, G Karypis, T Chilimbi… - arXiv preprint arXiv …, 2022"],"snippet":"… We evaluate the performance of SMILE by pre-training on the “Colossal Clean Crawled Corpus” (C4), a collection of English-language text sourced from the public Common Crawl web scrape. It includes heuristics to extract only natural language (as …","url":["https://arxiv.org/pdf/2212.05191"]}
+{"year":"2022","title":"Smooth inverse frequency based text data selection for medical dictation","authors":["D Bálint, P Mihajlik"],"snippet":"Under-resourced domain problem is significant in automatic speech recognition, especially in small languages such as Hungarian or in fields where data is often confidential such as finance and medicine. We introduce a method using word …","url":["http://acta.bibl.u-szeged.hu/73371/1/msznykonf_017_233-242.pdf"]}
+{"year":"2022","title":"SMTCE: A Social Media Text Classification Evaluation Benchmark and BERTology Models for Vietnamese","authors":["LT Nguyen, K Van Nguyen, NLT Nguyen - arXiv preprint arXiv:2209.10482, 2022"],"snippet":"Text classification is a typical natural language processing or computational linguistics task with various interesting applications. As the number of users on social media platforms increases, data acceleration promotes emerging studies on …","url":["https://arxiv.org/pdf/2209.10482"]}
+{"year":"2022","title":"Social and Web presence of Cultural Heritage Organisations in India","authors":["H Singh, M Gupta - 2022"],"snippet":"The present study focuses on the Social and Web presence of 27 Cultural Heritage Organisations in India. The purpose of this study is to investigate the domain authority, number of webpages, links, calculate the web impact factors and link-mentions …","url":["https://www.researchgate.net/profile/Mansi-Gupta-45/publication/362076832_Social_and_Web_presence_of_Cultural_Heritage_Organisations_in_India/links/62d583c8bf4b98532231ac8e/Social-and-Web-presence-of-Cultural-Heritage-Organisations-in-India.pdf"]}
+{"year":"2022","title":"SoK: On the Impossible Security of Very Large Foundation Models","authors":["EM El-Mhamdi, S Farhadkhani, R Guerraoui, N Gupta… - arXiv preprint arXiv …, 2022"],"snippet":"Large machine learning models, or so-called foundation models, aim to serve as base-models for application-oriented machine learning. Although these models showcase impressive performance, they have been empirically found to pose …","url":["https://arxiv.org/pdf/2209.15259"]}
+{"year":"2022","title":"Solving Hungarian natural language processing tasks with multilingual generative models","authors":["ZG Yang, LJ Laki"],"snippet":"Generative ability is a crucial need for artificial intelligence applications, such as chatbots, virtual assistants, machine translation systems etc. In recent years, the transformer-based neural architectures gave a huge boost to generate human-like …","url":["https://ami.uni-eszterhazy.hu/uploads/papers/finalpdf/AMI_online_1322.pdf"]}
+{"year":"2022","title":"Some Languages are More Equal than Others: Probing Deeper into the Linguistic Disparity in the NLP World","authors":["S Ranathunga, N de Silva - arXiv preprint arXiv:2210.08523, 2022"],"snippet":"Linguistic disparity in the NLP world is a problem that has been widely acknowledged recently. However, different facets of this problem, or the reasons behind this disparity are seldom discussed within the NLP community. This paper …","url":["https://arxiv.org/pdf/2210.08523"]}
+{"year":"2022","title":"SOS: Systematic Offensive Stereotyping Bias in Word Embeddings","authors":["F Elsafoury, SR Wilson, S Katsigiannis, N Ramzan"],"snippet":"Systematic Offensive stereotyping (SOS) in word embeddings could lead to associating marginalised groups with hate speech and profanity, which might lead to blocking and silencing those groups, especially on social media platforms. In this …","url":["https://efatmae.github.io/files/publications/2022/SOS_2022/SOS_bias_paper.pdf"]}
+{"year":"2022","title":"SPARQL querying for validating the usage of automatically georeferenced social media data as human sensors for air quality","authors":["S Andreadis, T Mavropoulos, N Pantelidis, S Vrochidis… - 2022 IEEE 14th Image …, 2022"],"snippet":"… original XLM model, XLM-R drew inspiration from RoBERTa [19], in the sense that it was trained for a longer time on more data, ie more than 2TBs of filtered CommonCrawl data. Since the tweets collection relates to the German language, a …","url":["https://2022.ivmsp.org/wp-content/uploads/2022/06/2022101087_IVMSP2022_CR_Copyright.pdf"]}
+{"year":"2022","title":"SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts","authors":["NTH Nguyen, PPD Ha, LT Nguyen, K Van Nguyen… - arXiv preprint arXiv …, 2022"],"snippet":"Question answering (QA) systems have gained explosive attention in recent years. However, QA tasks in Vietnamese do not have many datasets. Significantly, there is mostly no dataset in the medical domain. Therefore, we built a Vietnamese …","url":["https://arxiv.org/pdf/2206.09600"]}
+{"year":"2022","title":"Speculative Propositions for Digital Writing Under the New Autonomous Model of Literacy","authors":["B Robinson - Postdigital Science and Education, 2022"],"snippet":"The proliferation of powerful new forms of automated assistive writing technologies, natural language generation technologies in particular, raises crucial questions about the future of literacy living and learning. This article situates such technologies …","url":["https://link.springer.com/article/10.1007/s42438-022-00358-5"]}
+{"year":"2022","title":"Speech-to-Speech Translation For A Real-world Unwritten Language","authors":["PJ Chen, K Tran, Y Yang, J Du, J Kao, YA Chung… - arXiv preprint arXiv …, 2022"],"snippet":"… With the trained text and speech encoders, we perform data mining between Hokkien speech from Hokkien dramas and English Common Crawl text, and between the former and Librivox English audio7. We post-process the mined data in …","url":["https://arxiv.org/pdf/2211.06474"]}
+{"year":"2022","title":"SpeechMatrix: A Large-Scale Mined Corpus of Multilingual Speech-to-Speech Translations","authors":["PA Duquenne, H Gong, N Dong, J Du, A Lee… - arXiv preprint arXiv …, 2022"],"snippet":"We present SpeechMatrix, a large-scale multilingual corpus of speech-to-speech translations mined from real speech of European Parliament recordings. It contains speech alignments in 136 language pairs with a total of 418 thousand hours of …","url":["https://arxiv.org/pdf/2211.04508"]}
+{"year":"2022","title":"Speeding up Inference Time of Neural Machine Translation","authors":["M GELETKA"],"snippet":"Large qualitative gains were recently made in machine translation tasks thanks to Transformers models. However, in practice, these models suffer from high latency, such that they often are hardly usable in practical applications. This thesis study …","url":["https://is.muni.cz/th/if8vh/speeding_up_NMT_final.pdf"]}
+{"year":"2022","title":"Stability of a Multilingual Sentiment Analysis based on Word-to-Word Translations","authors":["N Horibe, K Fujihira - International Journal of Service and Knowledge …, 2022"],"snippet":"People’s sentiments are known to have a large impact on changes in stock prices, products sales, and trends. Since web users generally state their opinion in various languages, it is important to develop a method of multilingual sentiment analysis for …","url":["https://iaiai.org/journals/index.php/IJSKM/article/download/664/531"]}
+{"year":"2022","title":"Stacked Model based Argument Extraction and Stance Detection using Embedded LSTM model","authors":["P Rajula, CC Hung, SP Ponzetto - Working Notes Papers of the CLEF, 2022"],"snippet":"In this paper, we present our submission approach for the third Touché lab at CLEF 2022 [1], shared task 2 on Argument Retrieval for Comparative Questions, which tackles answering comparative questions based on argument retrieval of text …","url":["http://ceur-ws.org/Vol-3180/paper-258.pdf"]}
+{"year":"2022","title":"Stance Detection of Political Tweets with Transformer Architectures","authors":["P Gunhal, A Bashyam, K Zhang, A Koster, J Huang…"],"snippet":"The online actions and words of a person can reveal their political sentiments and how they may vote at the polls. For decades, the dominant strategy of determining voter sentiment on policies relied on slow and often inaccurate polling. The creation …","url":["https://journal-home.s3.ap-northeast-2.amazonaws.com/site/ictc2022/abs/EW4-21.pdf"]}
+{"year":"2022","title":"State-of-the-art in Open-domain Conversational AI: A Survey","authors":["T Adewumi, F Liwicki, M Liwicki - arXiv preprint arXiv:2205.00965, 2022"],"snippet":"We survey SoTA open-domain conversational AI models with the purpose of presenting the prevailing challenges that still exist to spur future research. In addition, we provide statistics on the gender of conversational AI in order to guide the ethics …","url":["https://arxiv.org/pdf/2205.00965"]}
+{"year":"2022","title":"Stateful Memory-Augmented Transformers for Dialogue Modeling","authors":["Q Wu, Z Yu - arXiv preprint arXiv:2209.07634, 2022"],"snippet":"Transformer encoder-decoder models have shown impressive performance in dialogue modeling. However, as Transformers are inefficient in processing long sequences, dialogue history length often needs to be truncated. To address this …","url":["https://arxiv.org/pdf/2209.07634"]}
+{"year":"2022","title":"Statistical Dataset Evaluation: Reliability, Difficulty, and Validity","authors":["C Wang, Q Dong, X Wang, H Wang, Z Sui - arXiv preprint arXiv:2212.09272, 2022"],"snippet":"Datasets serve as crucial training resources and model performance trackers. However, existing datasets have exposed a plethora of problems, inducing biased models and unreliable evaluation results. In this paper, we propose a model-agnostic …","url":["https://arxiv.org/pdf/2212.09272"]}
+{"year":"2022","title":"Statistical detection of format dialects using the weighted Dowker complex","authors":["M Robinson, LW Li, C Anderson, S Huntsman - arXiv preprint arXiv:2201.08267, 2022"],"snippet":"… The good files were largely sourced from Common Crawl [15], while the bad files were drawn from various … sources: some were found in the wild (from Common Crawl), some were malicious files created by the Test and Evaluation Team, and …","url":["https://arxiv.org/pdf/2201.08267"]}
+{"year":"2022","title":"StoryNet: A 5W1H-Based Knowledge Graph to Connect Stories","authors":["SR Nagireddy - 2021"],"snippet":"Stories are a powerful medium through which the human community has exchanged information since the dawn of the information age. They have taken multiple forms like articles, movies, books, plays, short films, magazines, mythologies, etc. With the …","url":["https://search.proquest.com/openview/19566ca4aa369437c6fc323d788f8739/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation","authors":["N Verma, K Murray, K Duh"],"snippet":"Pretrained multilingual sequence-to-sequence models have been successful in improving translation performance for mid-and lower-resourced languages. However, it is unclear if these models are helpful in the domain adaptation setting, and if so …","url":["https://www.cs.jhu.edu/~kevinduh/papers/verma22adapt.pdf"]}
+{"year":"2022","title":"Streaming neural machine translation systems from English into European languages","authors":["G Calabuig Doménech - 2022"],"snippet":"[EN] Machine translation is one of the most active areas within Artificial Intelligence, particularly in the field of Machine Learning. Recently, this area has been the focus of attention by major technology figures such as Google, Facebook, Microsoft, etc …","url":["https://riunet.upv.es/bitstream/handle/10251/187628/Calabuig%20-%20Streaming%20neural%20machine%20translation%20systems%20from%20English%20into%20European%20languages.pdf?sequence=1"]}
+{"year":"2022","title":"Streaming neural machine translation systems from European languages into English","authors":["AM Sarvazyan - 2022"],"snippet":"[EN] Machine translation is one of the most active areas within Artificial Intelligence, particularly in the field of Machine Learning. Recently, this area has been the focus of attention by major technology figures such as Google, Facebook, Microsoft, etc …","url":["https://riunet.upv.es/bitstream/handle/10251/185271/Sarvazyan%20-%20Streaming%20neural%20machine%20translation%20systems%20from%20European%20languages%20into%20English.pdf?sequence=1"]}
+{"year":"2022","title":"Streaming, fast and accurate on-device Inverse Text Normalization for Automatic Speech Recognition","authors":["Y Gaur, N Kibre, J Xue, K Shu, Y Wang, I Alphanso, J Li… - arXiv preprint arXiv …, 2022"],"snippet":"… The data is drawn from a coprora of email text, a collection of email addresses, common crawl data, and search queries. The selection of data from common crawl is loosely constrained to ITN-relevant strings, with some heuristics to avoid “mis-formatted” …","url":["https://arxiv.org/pdf/2211.03721"]}
+{"year":"2022","title":"Stress Detection from Social Media Articles: New Dataset Benchmark and Analytical Study","authors":["A Rastogi, Q Liu, E Cambria"],"snippet":"Stress detection is a basic and essential task for examining the mental health of a given population. With the rapid digitalization leading to text-based forms of communication gaining dominance over spoken ones, there is now the chance to …","url":["https://sentic.net/stress-detection-from-social-media.pdf"]}
+{"year":"2022","title":"Subspace-based Set Operations on a Pre-trained Word Embedding Space","authors":["Y Ishibashi, S Yokoi, K Sudoh, S Nakamura - arXiv preprint arXiv:2210.13034, 2022"],"snippet":"Word embedding is a fundamental technology in natural language processing. It is often exploited for tasks using sets of words, although standard methods for representing word sets and set operations remain limited. If we can leverage the …","url":["https://arxiv.org/pdf/2210.13034"]}
+{"year":"2022","title":"Subword-based Cross-lingual Transfer of Embeddings from Hindi to Marathi and Nepali","authors":["N Bafna, Z Žabokrtský - Proceedings of the 19th SIGMORPHON Workshop on …, 2022"],"snippet":"Word embeddings are growing to be a crucial resource in the field of NLP for any language. This work introduces a novel technique for static subword embeddings transfer for Indic languages from a relatively higher resource language to a …","url":["https://aclanthology.org/2022.sigmorphon-1.7.pdf"]}
+{"year":"2022","title":"SummVD: An efficient approach for unsupervised topic-based text summarization","authors":["G Shenouda, A Bossard, O Ayoub, C Rodrigues - … of the 2nd Conference of the Asia …, 2022"],"snippet":"This paper introduces a new method, SummVD, for automatic unsupervised extractive summarization. This method is based on singular value decomposition, a linear method in the number of words, in order to reduce the dimensionality of word …","url":["https://aclanthology.org/2022.aacl-main.38.pdf"]}
+{"year":"2022","title":"SumREN: Summarizing Reported Speech about Events in News","authors":["RG Reddy, H Elfardy, HP Chan, K Small, H Ji - arXiv preprint arXiv:2212.01146, 2022"],"snippet":"… We then collected a list of news articles discussing these events and retained articles that are present in Common Crawl (CC) News.We ended up with a total of 633 news articles corresponding to 132 major events. …","url":["https://arxiv.org/pdf/2212.01146"]}
+{"year":"2022","title":"Survey of NLP in Pharmacology: Methodology, Tasks, Resources, Knowledge, and Tools","authors":["D Trajanov, V Trajkovski, M Dimitrieva, J Dobreva… - arXiv preprint arXiv …, 2022"],"snippet":"Natural language processing (NLP) is an area of artificial intelligence that applies information technologies to process the human language, understand it to a certain degree, and use it in various applications. This area has rapidly developed in the …","url":["https://arxiv.org/pdf/2208.10228"]}
+{"year":"2022","title":"Survey on bimodal speech emotion recognition from acoustic and linguistic information fusion","authors":["BT Atmaja, A Sasou, M Akagi - Speech Communication, 2022"],"snippet":"Speech emotion recognition (SER) is traditionally performed using merely acoustic information. Acoustic features, commonly are extracted per frame, are mapped into emotion labels using classifiers such as support vector machines for machine …","url":["https://www.sciencedirect.com/science/article/pii/S0167639322000413"]}
+{"year":"2022","title":"Symptom or culprit? Social media, air pollution, and violence","authors":["X Du - 2022"],"snippet":"This paper provides the first causal evidence that hostile activities online lead to physical violence. Given the recently documented relationship between pollution and social media, I exploit exogenous variation in local air quality as the first step to …","url":["https://www.sipa.columbia.edu/sites/default/files/2022-11/draft20_1104.pdf"]}
+{"year":"2022","title":"SYNONYM DETECTION USING SYNTACTIC DEPENDENCY AND NEURAL EMBEDDINGS","authors":["D Yang, P Wang, X Sun, N Li"],"snippet":"Recent advances on the Vector Space Model have significantly improved some NLP applications such as neural machine translation and natural language generation. Although word co-occurrences in context have been widely used in counting-/predicting-based …","url":["http://www.iadisportal.org/ijwi/papers/202220102.pdf"]}
+{"year":"2022","title":"Synopses of Movie Narratives: a Video-Language Dataset for Story Understanding","authors":["Y Sun, Q Chao, B Li - arXiv preprint arXiv:2203.05711, 2022"],"snippet":"Despite recent advances of AI, story understanding remains an open and under-investigated problem. We collect, preprocess, and publicly release a video-language story dataset, Synopses of Movie Narratives(SyMoN), containing 5,193 video summaries …","url":["https://arxiv.org/pdf/2203.05711"]}
+{"year":"2022","title":"Synthesis and Evaluation of a Domain-specific Large Data Set for Dungeons & Dragons","authors":["A Peiris, N de Silva - arXiv preprint arXiv:2212.09080, 2022"],"snippet":"This paper introduces the Forgotten Realms Wiki (FRW) data set and domain specific natural language generation using FRW along with related analyses. Forgotten Realms is the de-facto default setting of the popular open ended tabletop …","url":["https://arxiv.org/pdf/2212.09080"]}
+{"year":"2022","title":"Table Pretraining: A Survey on Model Architectures, Pretraining Objectives, and Downstream Tasks","authors":["H Dong, Z Cheng, X He, M Zhou, A Zhou, F Zhou, A Liu… - arXiv preprint arXiv …, 2022"],"snippet":"Since a vast number of tables can be easily collected from web pages, spreadsheets, PDFs, and various other document types, a flurry of table pretraining frameworks have been proposed following the success of text and images, and they have …","url":["https://arxiv.org/pdf/2201.09745"]}
+{"year":"2022","title":"Tackling Social Value Tasks with Multilingual NLP","authors":["MR Awal - 2022"],"snippet":"In recent years, deep learning applications have shown promise in tackling social value tasks such as hate speech and misinformation in social media. Neural networks provide an efficient automated solution that has replaced hand-engineered …","url":["https://harvest.usask.ca/bitstream/handle/10388/14394/AWAL-THESIS-2022.pdf?sequence=1&isAllowed=y"]}
+{"year":"2022","title":"TAG: Learning Circuit Spatial Embedding From Layouts","authors":["K Zhu, H Chen, WJ Turner, GF Kokai, PH Wei, DZ Pan… - arXiv preprint arXiv …, 2022"],"snippet":"Analog and mixed-signal (AMS) circuit designs still rely on human design expertise. Machine learning has been assisting circuit design automation by replacing human experience with artificial intelligence. This paper presents TAG, a new paradigm of …","url":["https://arxiv.org/pdf/2209.03465"]}
+{"year":"2022","title":"Tagging terms in text","authors":["AR Terryn, V Hoste, E Lefever"],"snippet":"… We used the embeddings that are pre-trained on Common Crawl (for all languages). Finally, the hugely successful transformer-based architectures are supported in FlairNLP as well, through HuggingFace (Wolf et al. …","url":["https://www.researchgate.net/profile/Ayla_Rigouts_Terryn2/publication/356283802_Tagging_terms_in_text_A_supervised_sequential_labelling_approach_to_automatic_term_extraction/links/61f00c02c5e3103375bd750b/Tagging-terms-in-text-A-supervised-sequential-labelling-approach-to-automatic-term-extraction.pdf"]}
+{"year":"2022","title":"Talk to me: Database Vocalization Summaries using BART and PEGASUS","authors":["A Elkhouly, P Joshi, S Rathod, S Aziz, V Kalra…"],"snippet":"Zeta bytes of data are generated on a daily basis and this is growing continuously. Naturally, it is imperative for all kinds of stakeholders to have tools that help them gain insights into this data. So far text summarization work has been done using …","url":["https://www.academia.edu/download/78533097/TalkToMe1620511162956.pdf"]}
+{"year":"2022","title":"TamilEmo: Finegrained Emotion Detection Dataset for Tamil","authors":["C Vasantharajan, S Benhur, PK Kumarasen… - arXiv preprint arXiv …, 2022"],"snippet":"Emotional Analysis from textual input has been considered both a challenging and interesting task in Natural Language Processing. However, due to the lack of datasets in low-resource languages (ie Tamil), it is difficult to conduct research of …","url":["https://arxiv.org/pdf/2202.04725"]}
+{"year":"2022","title":"Tasks Using the Hugging Face Library","authors":["SM Jain - Introduction to Transformers for NLP, 2022"],"snippet":"… It produces a tidier version of the enormous Common Crawl dataset, which is referred to as the Colossal Cleaned Common Crawl (C4) . This dataset is approximately 100,000 times more extensive than Wikipedia. … It prepares the body …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-8844-3_5"]}
+{"year":"2022","title":"TaTa: A Multilingual Table-to-Text Dataset for African Languages","authors":["S Gehrmann, S Ruder, V Nikolaev, JA Botha… - arXiv preprint arXiv …, 2022"],"snippet":"Existing data-to-text generation datasets are mostly limited to English. To address this lack of data, we create Table-to-Text in African languages (TaTa), the first large multilingual table-to-text dataset with a focus on African languages. We created …","url":["https://arxiv.org/pdf/2211.00142"]}
+{"year":"2022","title":"Teaching AI when to care about gender","authors":["J Powell, K Sentz, E Moyer, M Klein - Code4Lib Journal, 2022"],"snippet":"… For many deep learning/NLP tasks, it is standard practice to download pre-trained models such as GoogleNews, Common Crawl, and wikipedia word embeddings models and use them for deep learning tasks. Since pretrained models are trained …","url":["https://journal.code4lib.org/articles/16718"]}
+{"year":"2022","title":"Technical Report on Web-based Visual Corpus Construction for Visual Document Understanding","authors":["D Kim, T Hong, M Yim, Y Kim, G Kim - arXiv preprint arXiv:2211.03256, 2022"],"snippet":"We present a dataset generator engine named Web-based Visual Corpus Builder (Webvicob). Webvicob can readily construct a large-scale visual corpus (ie, images with text annotations) from a raw Wikipedia HTML dump. In this report, we validate that …","url":["https://arxiv.org/pdf/2211.03256"]}
+{"year":"2022","title":"Technology behind text to image generators","authors":["P Fernandez - Library Hi Tech News, 2022"],"snippet":"… Common Crawl, which has petabytes of data taken by scraping websites. Copyright law in the USA can be frustratingly ambiguous, but factors in Common Crawl’s … In other words, Common Crawl creates large data sets used for …","url":["https://www.emerald.com/insight/content/doi/10.1108/LHTN-10-2022-0116/full/html"]}
+{"year":"2022","title":"Technology, Vintage-Specific Human Capital, and Labor Displacement: Evidence from Linking Patents with Occupations","authors":["L Kogan, D Papanikolaou, LDW Schmidt, B Seegmiller"],"snippet":"We develop a granular, occupation-specific measure of technological progress that relies only on textual descriptions of patent documents and the tasks performed by workers in an occupation. Our measure primarily identifies labor-saving innovations …","url":["https://www.bryanseegmiller.com/files/Draft_v2022-07.pdf"]}
+{"year":"2022","title":"Test collections for web-scale datasets using Dynamic Sampling","authors":["A Singh - 2022"],"snippet":"… Other large scale web collections, like the Common Crawl dataset, have also been used in various TREC tracks. It might be interesting to study the performance of Dynamic Sampling on these alternate datasets like Common Crawl1. Additionally, in …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/17889/Singh_Anmol.pdf?sequence=3"]}
+{"year":"2022","title":"TeSum: Human-Generated Abstractive Summarization Corpus for Telugu","authors":["A Urlana, N Surange, P Baswani, P Ravva…"],"snippet":"Expert human annotation for summarization is definitely an expensive task, and can not be done on huge scales. But with this work, we show that even with a crowd sourced summary generation approach, quality can be controlled by aggressive …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.614.pdf"]}
+{"year":"2022","title":"Text Algorithms in Economics","authors":["E Ash, S Hansen - 2022"],"snippet":"This paper provides an overview of the methods used for algorithmic text analysis in economics, with a focus on three key contributions. First, the paper introduces methods for representing documents as high-dimensional count vectors over …","url":["https://elliottash.com/wp-content/uploads/2022/08/annual_reviews_chapter-2022-08-16.pdf"]}
+{"year":"2022","title":"Text Analysis of Airline Tweets","authors":["E ALTamimi - 2022"],"snippet":"… For the FastText approach, we used gensim to load the vector file from the common crawl models downloaded from fasttext (FastText, 2020) and converted it to a bin model because the loading time of the vector was more. We then continued to …","url":["https://scholarworks.rit.edu/cgi/viewcontent.cgi?article=12309&context=theses"]}
+{"year":"2022","title":"Text Characterization Toolkit (TCT)","authors":["D Simig, T Wang, V Dankers, P Henderson, K Batsuren… - … of the 2nd Conference of the …, 2022"],"snippet":"We present a tool, Text Characterization Toolkit (TCT), that researchers can use to study characteristics of large datasets. Furthermore, such properties can lead to understanding the influence of such attributes on models’ behaviour. Traditionally, in …","url":["https://aclanthology.org/2022.aacl-demo.9.pdf"]}
+{"year":"2022","title":"Text Characterization Toolkit","authors":["D Simig, T Wang, V Dankers, P Henderson, K Batsuren… - arXiv preprint arXiv …, 2022"],"snippet":"In NLP, models are usually evaluated by reporting single-number performance scores on a number of readily available benchmarks, without much deeper analysis. Here, we argue that - especially given the well-known fact that benchmarks often …","url":["https://web7.arxiv.org/pdf/2210.01734"]}
+{"year":"2022","title":"Text Embeddings by Weakly-Supervised Contrastive Pre-training","authors":["L Wang, N Yang, X Huang, B Jiao, L Yang, D Jiang… - arXiv preprint arXiv …, 2022"],"snippet":"… data sources such as CommunityQA, Common Crawl and Scientific papers, and perform … Simple heuristic rules are applied to filter data from Reddit and Common Crawl. For example, … Reddit and Common Crawl. For more details and examples …","url":["https://arxiv.org/pdf/2212.03533"]}
+{"year":"2022","title":"Text Representations and Word Embeddings","authors":["R Egger - Applied Data Science in Tourism, 2022"],"snippet":"Today, a vast amount of unstructured text data is consistently at our disposal. Owing to the rapid increase in user-generated content on the one hand and powerful, ready-to-use machine learning algorithms on the other hand, automated text analysis can now be …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88389-8_16"]}
+{"year":"2022","title":"Text to Image GANs with RoBERTa and Fine-grained Attention Networks","authors":["M Siddharth, R Aarthi"],"snippet":"… The additional data included CommonCrawl News dataset, Web text corpus and Stories from Common Crawl. The RoBERTa makes use of similar architecture as BERT Model but uses the byte-level BPE as the tokenizer [4]. The ’roberta-base’ is …","url":["https://www.researchgate.net/profile/Siddharth-M/publication/357450869_Text_to_Image_GANs_with_RoBERTa_and_Fine-grained_Attention_Networks/links/61d2bb43e669ee0f5c8185bb/Text-to-Image-GANs-with-RoBERTa-and-Fine-grained-Attention-Networks.pdf"]}
+{"year":"2022","title":"Text Vectorization Method Based on Concept Mining Using Clustering Techniques","authors":["A Mansour, J Mohammad, Y Kravchenko - 2022 VI International Conference on …, 2022"],"snippet":"… word vectors trained with sub-word information on Wikipedia 2017, UMBC webbase corpus, and statmt.org news data set (16B tokens); word2vec model2 which was trained with Google News corpus (3 billion words) and Glove model …","url":["https://ieeexplore.ieee.org/abstract/document/9782908/"]}
+{"year":"2022","title":"Text-to-Text Transfer Transformer Phrasing Model Using Enriched Text Input","authors":["M Řezáčková, J Matoušek - International Conference on Text, Speech, and …, 2022"],"snippet":"… In our experiments, we used the Text-to-Text Transfer Transformer (T5) model (following the architecture presented in [16, 25]) pre-trained from a huge amount of unlabeled text from the Czech CommonCrawl corpus [27]. For training the model itself, we used …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_32"]}
+{"year":"2022","title":"Textual Inference Identification in the Malayalam Language Using Convolutional Neural Network","authors":["S Renjit, SM Idicula - Advanced Computing and Intelligent Technologies, 2022"],"snippet":"… fastText [11] has a collection of pre-trained word vectors in 157 languages, where each language word collection is from Wikipedia and common crawl. Such collections provide a good start for language processing tasks in low-resource …","url":["https://link.springer.com/chapter/10.1007/978-981-19-2980-9_20"]}
+{"year":"2022","title":"The (Moral) Language of Hate","authors":["B Kennedy, P Golazizian, J Trager, M Atari, J Hoover… - 2022"],"snippet":"… In the present study, we extract the FastText embeddings — via the pre-trained set of embeddings10, which are trained on a combination of Wikipedia and Common Crawl data — of terms in the Weaponized Word lexicon, for the 19 …","url":["https://psyarxiv.com/eqp34/download?format=pdf"]}
+{"year":"2022","title":"THE ADVANCE TECHNIQUES USED IN CYBER SECURITY FOR PHISHING DETECTION","authors":["P Chate, MS Maske, MS Maske"],"snippet":"The Internet has become a necessary part of our lives; however, it has also provided opportunities to carry out malicious activities anonymously like Phishing. Phishers try to trick their victims through social engineering or create mock-up websites to …","url":["https://www.researchgate.net/profile/Parinita-Chate-2/publication/362539921_THE_ADVANCE_TECHNIQUES_USED_IN_CYBER_SECURITY_FOR_PHISHING_DETECTION/links/62efc6874532247693889dd0/THE-ADVANCE-TECHNIQUES-USED-IN-CYBER-SECURITY-FOR-PHISHING-DETECTION.pdf"]}
+{"year":"2022","title":"The AISP-SJTU Translation System for WMT 2022","authors":["G Liu, Q Zhu, X Chen, R Feng, J Ren, R Wu, Q Miao… - Proceedings of the Seventh …, 2022","GLQZX Chen, RFJRR Wu, QMRWK Yu"],"snippet":"… For monolingual data, we select data from News Crawl, Common Crawl and Extended Common Crawl, and the amount of data after pro… Crawl and Common Crawl. Then we used the JA-EN ensemble model to generate the hypotheses as the …","url":["https://aclanthology.org/2022.wmt-1.24.pdf","https://www.statmt.org/wmt22/pdf/2022.wmt-1.24.pdf"]}
+{"year":"2022","title":"The case for 4-bit precision: k-bit Inference Scaling Laws","authors":["T Dettmers, L Zettlemoyer - arXiv preprint arXiv:2212.09720, 2022"],"snippet":"… Furthermore, we find that across more than 35,000 zero-shot experiments, the Pearson correlation coefficient between The Pile Common Crawl perplexity and zero-shot performance is -0.94. … In this section, we present data for evaluation on The Pile …","url":["https://arxiv.org/pdf/2212.09720"]}
+{"year":"2022","title":"The Causal News Corpus: Annotating Causal Relations in Event Sentences from News","authors":["FA Tan, A Hürriyetoğlu, T Caselli, N Oostdijk, T Nomoto… - arXiv preprint arXiv …, 2022"],"snippet":"Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on linguistics …","url":["https://arxiv.org/pdf/2204.11714"]}
+{"year":"2022","title":"The Curious Case of Control","authors":["E Stengel-Eskin, B Van Durme - arXiv preprint arXiv:2205.12113, 2022"],"snippet":"… The training data is based on Common Crawl, though similarly to GPT-3 Davinci, the details of the training data filtering process are unclear. Relevant differences to GPT-3 are in the tokenization (which includes multi-word expressions) and use of …","url":["https://arxiv.org/pdf/2205.12113"]}
+{"year":"2022","title":"The Dark Side of the Language: Pre-trained Transformers in the DarkNet","authors":["L Ranaldi, A Nourbakhsh, A Patrizi, ES Ruzzetti… - arXiv preprint arXiv …, 2022"],"snippet":"Pre-trained Transformers are challenging human performances in many natural language processing tasks. The gigantic datasets used for pre-training seem to be the key for their success on existing tasks. In this paper, we explore how a range of …","url":["https://arxiv.org/pdf/2201.05613"]}
+{"year":"2022","title":"The Effect of Pre-trained Language Models on Critical Case Detection from Radiology Reports","authors":["G BAYRAK, MS TOPRAK, MC GANIZ, H KODAZ…"],"snippet":"… As the embedding layer of the bi-LSTM we use following alternatives: 1) fastText pre-trained model for Turkish on common crawl 3 2) fastText model trained from scratch using our unsupervised dataset of 190 thousand radiology reports 3) BERT …","url":["https://www.researchgate.net/profile/Murat-Ganiz/publication/363413813_The_Effect_of_Pre-trained_Language_Models_on_Critical_Case_Detection_from_Radiology_Reports/links/631b4ce8873eca0c007514fd/The-Effect-of-Pre-trained-Language-Models-on-Critical-Case-Detection-from-Radiology-Reports.pdf"]}
+{"year":"2022","title":"The emergence of gender associations in child language development","authors":["B Prystawski, E Grant, A Nematzadeh, SWS Lee…"],"snippet":"Gender associations have been a long-standing research topic in psychological and social sciences. Although it is known that children learn aspects of gender association at a young age, it is not well understood how they might emerge through …","url":["https://www.researchgate.net/profile/Yang-Xu-34/publication/360554719_The_emergence_of_gender_associations_in_child_language_development/links/627d55beb1ad9f66c8b8563c/The-emergence-of-gender-associations-in-child-language-development.pdf"]}
+{"year":"2022","title":"The fujitsu dmath submissions for wmt21 news translation and biomedical translation tasks","authors":["A Martínez - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"… For example, we noted that the Hausa Extended Common Crawl corpus published for WMT21 contained a large number of Japanese … Despite its noisy nature, we decided to use the Extended Common Crawl Hausa corpus. The results …","url":["https://aclanthology.org/2021.wmt-1.13.pdf"]}
+{"year":"2022","title":"The Ghost in the Machine has an American accent: value conflict in GPT-3","authors":["RL Johnson, G Pistilli, N Menédez-González… - arXiv preprint arXiv …, 2022"],"snippet":"The alignment problem in the context of large language models must consider the plurality of human values in our world. Whilst there are many resonant and overlapping values amongst the world's cultures, there are also many conflicting, yet …","url":["https://arxiv.org/pdf/2203.07785"]}
+{"year":"2022","title":"The hitchhiker's guide Method handbook for quantification of online lin-guistic data in a country-specific context Official research report, Linguistic Explorations of …","authors":["J Andersson Schwarz - 2022"],"snippet":"… A very significant non-profit provider to consider alongside these commercial actors is CommonCrawl (USA). As for CrowdTangle and DataSift… The CommonCrawl corpus contains petabytes of data including raw web page data …","url":["https://gupea.ub.gu.se/bitstream/handle/2077/70890/2022_1_Andersson%20Schwarz.pdf?sequence=1"]}
+{"year":"2022","title":"The hitchhiker's guide to web-mediated text. Method handbook for quantification of online linguistic data in a country-specific context. Official research report …","authors":["J Andersson Schwarz - 2022"],"snippet":"… While a data provider could be any entity, also nonprofit or government-funded ones (CommonCrawl is one such example, described in more detail below), a vendor is typically a company operating in sectors like market intelligence, social …","url":["https://gupea.ub.gu.se/bitstream/handle/2077/70866/2022_1_Andersson%20Schwarz.pdf?sequence=1"]}
+{"year":"2022","title":"The IARPA BETTER Program Abstract Task Four New Semantically Annotated Corpora from IARPA's BETTER Program","authors":["C Rubino, T McKinnon"],"snippet":"… In Phase I, sentences were randomly chosen from newswire texts in the target languages harvested from the Common Crawl. An Amazon Mechanical Turk pipeline was set up to confirm the suitability of the extracted sentences according to …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.384.pdf"]}
+{"year":"2022","title":"THE IMPACT OF ONLINE AFFILIATE MARKETING ON WEB SEARCH","authors":["J Bevendorff, M Wiegmann, M Potthast, B Stein"],"snippet":"… Based on several pageand domain-level text quality features, which we calculated at scale on four different Common Crawl versions, we … number of pages crawled from domains that fall into the “affiliate spam” genre might improve the quality of …","url":["https://webis.de/downloads/publications/papers/bevendorff_2022c.pdf"]}
+{"year":"2022","title":"The Increasing Frequency of Terms Denoting Political Extremism in US and UK News Media","authors":["D Rozado, E Kaufmann - Social Sciences, 2022"],"snippet":"The term political extremism is commonly used to refer to political attitudes considered to be outside the ideological mainstream. This study leverages computational content analysis of big data to longitudinally examine (1970–2019) …","url":["https://www.mdpi.com/2076-0760/11/4/167/pdf"]}
+{"year":"2022","title":"The Indeterminate Self and Large Language Models: A Nietzschean Critique of GPT-3","authors":["S Fischer - 2022"],"snippet":"… For GPT-3, the largest part of the training data (60%) comes from the web scraping repository Common Crawl12 (Brown et al., 2020, p. 9). The exact sources of the Common Crawl data set are not disclosed, and given the sheer amount it is …","url":["http://essay.utwente.nl/89754/1/Fischer_MA_BMS.pdf"]}
+{"year":"2022","title":"The Infinite Index: Information Retrieval on Generative Text-To-Image Models","authors":["N Deckers, M Fröbe, J Kiesel, G Pandolfo, C Schröder… - arXiv preprint arXiv …, 2022"],"snippet":"The text-to-image model Stable Diffusion has recently become very popular. Only weeks after its open source release, millions are experimenting with image generation. This is due to its ease of use, since all it takes is a brief description of the …","url":["https://arxiv.org/pdf/2212.07476"]}
+{"year":"2022","title":"The language of opinion change on social media under the lens of communicative action","authors":["C Monti, LM Aiello, G De Francisci Morales, F Bonchi - Scientific Reports, 2022"],"snippet":"Which messages are more effective at inducing a change of opinion in the listener? We approach this question within the frame of Habermas’ theory of communicative action, which posits that the illocutionary intent of the message (its pragmatic …","url":["https://www.nature.com/articles/s41598-022-21720-4"]}
+{"year":"2022","title":"The Minimum Wage as an Anchor: Effects on Determinations of Fairness by Humans and AI","authors":["DG Soatto - arXiv preprint arXiv:2210.10585, 2022"],"snippet":"I study the role of the minimum wage as an anchor for perceptions of the fairness of wages by both human subjects and AI. Through surveys on human subjects enrolled in the crowdsourcing platform Prolific.co and queries submitted to the large …","url":["https://arxiv.org/pdf/2210.10585"]}
+{"year":"2022","title":"The mininglamp machine translation system for wmt21","authors":["S Zhao, X Li, M Wu, J Hao - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"This paper describes Mininglamp neural machine translation systems of the WMT2021 news translation tasks. We have participated in eight directions translation tasks for news text including Chinese to/from English, Hausa to/from …","url":["https://aclanthology.org/2021.wmt-1.25.pdf"]}
+{"year":"2022","title":"The MORAL INTEGRITY CORPUS: A Benchmark for Ethical Dialogue Systems","authors":["C Ziems, AY Jane, YC Wang, A Halevy, D Yang"],"snippet":"Conversational agents have come increasingly closer to human competence in open-domain dialogue settings; however, such models often reflect insensitive, hurtful, or entirely incoherent viewpoints that erode a user’s trust in the moral integrity of the system …","url":["https://faculty.cc.gatech.edu/~dyang888/docs/acl22_moral.pdf"]}
+{"year":"2022","title":"The multiplex relations between cities: a lexicon-based approach to detect urban systems","authors":["W Tongjing, E Meijers, H Wang - Regional Studies, 2022"],"snippet":"… Common Crawl is one of the largest publicly available web archives, a … the Common Crawl web archive as our preliminary data source to avoid selection bias. We extracted a 139 Gigabyte text corpus containing 91 million Chinese webpages …","url":["https://www.tandfonline.com/doi/pdf/10.1080/00343404.2022.2120978"]}
+{"year":"2022","title":"The NiuTrans Machine Translation Systems for WMT22","authors":["W Shan, Z Cao, Y Han, S Wu, Y Hu, T Xiao, A Ma…"],"snippet":"This paper describes the NiuTrans neural machine translation systems of the WMT22 General MT constrained task. We participate in four directions, including Chinese→ English, English→ Croatian, and Livonian↔ English. Our models are …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.32.pdf"]}
+{"year":"2022","title":"The Norwegian Colossal Corpus: A Text Corpus for Training Large Norwegian Language Models","authors":["PE Kummervold, F Wetjen, J de la Rosa"],"snippet":"Norwegian has been one of many languages lacking sufficient available text to train quality language models. In an attempt to bridge this gap, we introduce the Norwegian Colossal Corpus (NCC), which comprises 49GB of clean Norwegian …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.410.pdf"]}
+{"year":"2022","title":"The only chance to understand: machine translation of the severely endangered low-resource languages of Eurasia","authors":["A Mossolova, K Smaïli - The Fifth Workshop on Technologies for Machine …, 2022"],"snippet":"Numerous machine translation systems have been proposed since the appearance of this task. Nowadays, new large language modelbased algorithms show results that sometimes overcome human ones on the rich-resource languages …","url":["https://hal.archives-ouvertes.fr/hal-03774644/file/final_loresmt_paper.pdf"]}
+{"year":"2022","title":"The Problem with XSD Binary Floating Point Datatypes in RDF","authors":["JM Keil, M Gänßinger"],"snippet":"… in the September 2020 Common Crawl archive,13 a freely available web crawl archive. We selected it because of its large size, an expected large proportion of literals, the uniform access of the whole corpus, its heterogeneous original sources (15e6domains) …","url":["https://2022.eswc-conferences.org/wp-content/uploads/2022/05/paper_98_Keil_et_al.pdf"]}
+{"year":"2022","title":"The Role of negative information when learning dense word vectors","authors":["AT Salle - 2021"],"snippet":"… Figure 1.1 shows a 2-dimensional PCA projection of a set of words vectors drawn from our LexVec Common Crawl vectors (the LexVec model is presented in Chapter 3), illustrating how a vector space model represents meaning. Words that are …","url":["https://www.lume.ufrgs.br/bitstream/handle/10183/234537/001136324.pdf?sequence=1"]}
+{"year":"2022","title":"The semantics of-ee and-ation: a distributional semantic approach","authors":["V Schneider"],"snippet":"… Common Crawl subword model • 2 million pre-trained word vectors • Contains subword information to create new vectors based on …","url":["https://viktoria-schneider.phil.hhu.de/wp-content/uploads/2022/11/Ingo-Birthday-22-09-01.pdf"]}
+{"year":"2022","title":"The Seventh Workshop on Search-Oriented Conversational Artificial Intelligence (SCAI'22)","authors":["G Penha, S Vakulenko, O Dusek, L Clark, V Pal… - Proceedings of the 45th …, 2022"],"snippet":"… The two datasets also differ with respect to the information source — QReCC has a larger and more diverse collection of 54M passages based on Commoncrawl, whereas TopiOCQA has 26M passages based on Wikipedia. While the corpus of …","url":["https://dl.acm.org/doi/pdf/10.1145/3477495.3531700"]}
+{"year":"2022","title":"The sins of the parents are to be laid upon the children: biased humans, biased data, biased models","authors":["M Osborne, A Omrani, M Dehghani - 2022"],"snippet":"Technological innovations have become a key driver of societal advancements. Nowhere is this more evident than in the field of machine learning (ML), which has developed algorithmic models that shape our decisions, behaviors, and outcomes …","url":["https://psyarxiv.com/4eqnk/download?format=pdf"]}
+{"year":"2022","title":"The State of Profanity Obfuscation in Natural Language Processing","authors":["D Nozza, D Hovy - arXiv preprint arXiv:2210.07595, 2022"],"snippet":"Work on hate speech has made the consideration of rude and harmful examples in scientific publications inevitable. This raises various problems, such as whether or not to obscure profanities. While science must accurately disclose what it does, the …","url":["https://arxiv.org/pdf/2210.07595"]}
+{"year":"2022","title":"The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task","authors":["ASSFK Nguyen, KBH Daumé III"],"snippet":"We describe the University of Maryland machine translation systems submitted to the WMT17 German-English Bandit Learning Task. The task is to adapt a translation system to a new domain, using only bandit feedback: the system receives a German …","url":["https://ar5iv.labs.arxiv.org/html/1708.01318"]}
+{"year":"2022","title":"The usefulness of NLP techniques for predicting peaks in firefighter interventions due to rare events","authors":["S Cerna, C Guyeux, D Laiymani - Neural Computing and Applications, 2022"],"snippet":"… This is mainly because the LSTM and CNN models were trained only with the vocabulary of the bulletins while the transformers were pre-trained with an extensive vocabulary of the French language (Common Crawl Oscar corpus). Thus, this set of …","url":["https://link.springer.com/article/10.1007/s00521-022-06996-x"]}
+{"year":"2022","title":"The VolcTrans System for WMT22 Multilingual Machine Translation Task","authors":["X Qian, K Hu, J Wang, Y Liu, X Pan, J Cao, M Wang - arXiv preprint arXiv:2210.11599, 2022"],"snippet":"This report describes our VolcTrans system for the WMT22 shared task on large-scale multilingual machine translation. We participated in the unconstrained track which allows the use of external resources. Our system is a transformerbased multilingual …","url":["https://arxiv.org/pdf/2210.11599"]}
+{"year":"2022","title":"The YiTrans End-to-End Speech Translation System for IWSLT 2022 Offline Shared Task","authors":["Z Zhang, J Ao - IWSLT 2022, 2022"],"snippet":"This paper describes the submission of our end-to-end YiTrans speech translation system for the IWSLT 2022 offline task, which translates from English audio to German, Chinese, and Japanese. The YiTrans system is built on large-scale pre-trained …","url":["https://aclanthology.org/2022.iwslt-1.pdf#page=168"]}
+{"year":"2022","title":"ThEconSum: an Economics-domained Dataset for Thai Text Summarization and Baseline Models","authors":["S Jumpathong, A Takhom, P Boonkwan… - 2022 17th International Joint …, 2022"],"snippet":"Language resources as datasets are an essential component in developing an effective automatic text summarization (ATS) system. Some public datasets are relatively uncommon when compared with popular languages, due to the complexity …","url":["https://ieeexplore.ieee.org/abstract/document/9960271/"]}
+{"year":"2022","title":"Thirumurai: A Large Dataset of Tamil Shaivite Poems and Classification of Tamil Pann","authors":["S Mahadevan, R Ponnusamy, PK Kumaresan…"],"snippet":"… Such models are trained on petabytes of data, such as the Common Crawl data, which has over 12 years of internet data. Due to the size of the data they are being trained on, this not only improves the accuracy of the models, but it also allows them …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.704.pdf"]}
+{"year":"2022","title":"Three-order normalized PMI and other lessons in tensor analysis of verbal selectional preferences","authors":["M Makrai"],"snippet":"We investigate several questions in transitive verb structure representation by decomposing tensors populated with different subject-verb-object association measures, including a novel generalization of normalized pointwise mutual …","url":["https://hlt.bme.hu/media/pdf/verbtensor_guxggK5.pdf"]}
+{"year":"2022","title":"TL; DR: Mining Reddit to Learn Automatic Summarization","authors":["R Logan"],"snippet":"Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data. We propose a …","url":["https://zdoc.pub/tldr-mining-reddit-to-learn-automatic-summarization.html"]}
+{"year":"2022","title":"To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering","authors":["D Dua, E Strubell, S Singh, P Verga - arXiv preprint arXiv:2212.10381, 2022"],"snippet":"… To understand the impact of the pre-trainining vs fine-tuning corpus, we also compare the performance of the FiD reader initialized from T5 pretrained on common-crawl dataset(C4) compared to one that was pre-trained on pubmed articles. After …","url":["https://arxiv.org/pdf/2212.10381"]}
+{"year":"2022","title":"Topic Classification in Indonesian-language Tweets using Fast-Text Feature Expansion with Support Vector Machine (SVM)","authors":["IM Fadhil, Y Sibaroni - 2022 International Conference on Data Science and Its …, 2022"],"snippet":"… The word vector used in this study uses a pretrained Indonesian word vector that can be used from research [7] where the corpus used to train the model comes from Wikipedia and Common Crawl with the number of words contained in the word …","url":["https://ieeexplore.ieee.org/abstract/document/9862899/"]}
+{"year":"2022","title":"Towards a Cleaner Document-Oriented Multilingual Crawled Corpus","authors":["J Abadji, PO Suarez, L Romary, B Sagot - arXiv preprint arXiv:2201.06642, 2022"],"snippet":"… Table 1: Comparison of occurrences of news-related terms between OSCAR and our corpus in a sample of 100 CommonCrawl shards. *: For the Burmese language, we use the whole 21.09 and 22.XX corpus since it is a low resource language …","url":["https://arxiv.org/pdf/2201.06642"]}
+{"year":"2022","title":"Towards Analyzing the Bias of News Recommender Systems Using Sentiment and Stance Detection","authors":["M Alam, A Iana, A Grote, K Ludwig, P Müller… - arXiv preprint arXiv …, 2022"],"snippet":"… More specifically, we use a pre-trained German word2vec model trained on the Common Crawl and Wikipedia dataset [12] to learn latent representations of the words in an article. The article’s vector representation is computed as the average of …","url":["https://arxiv.org/pdf/2203.05824"]}
+{"year":"2022","title":"Towards Arabic Sentence Simplification via Classification and Generative Approaches","authors":["N Khallaf, S Sharoff - arXiv preprint arXiv:2204.09292, 2022"],"snippet":"This paper presents an attempt to build a Modern Standard Arabic (MSA) sentence-level simplification system. We experimented with sentence simplification using two approaches: (i) a classification approach leading to lexical simplification pipelines …","url":["https://arxiv.org/pdf/2204.09292"]}
+{"year":"2022","title":"Towards Automatic Generation of Messages Countering Online Hate Speech and Microaggressions","authors":["M Ashida, M Komachi - Proceedings of the Sixth Workshop on Online Abuse …, 2022"],"snippet":"With the widespread use of social media, online hate is increasing, and microaggressions are receiving attention. We explore the potential for using pretrained language models to automatically generate messages that combat the …","url":["https://aclanthology.org/2022.woah-1.2.pdf"]}
+{"year":"2022","title":"Towards automatic generation of Piping and Instrumentation Diagrams (P&IDs) with Artificial Intelligence","authors":["E Hirtreiter, LS Balhorn, AM Schweidtmann - arXiv preprint arXiv:2211.05583, 2022"],"snippet":"Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during the development of chemical processes. Currently, this is a tedious, manual, and time-consuming task. We propose a novel, completely data-driven method for the …","url":["https://arxiv.org/pdf/2211.05583"]}
+{"year":"2022","title":"Towards better structured and less noisy Web data: Oscar with Register annotations","authors":["V Laippala, A Salmela, S Rönnqvist, AF Aji, LH Chang… - Proceedings of the Eighth …, 2022"],"snippet":"… The documents for the annotation were randomly sampled from a recent Common Crawl2 dataset. The annotation was done using a custom … The documents were retrieved from Common Crawl using the same pipeline as the …","url":["https://aclanthology.org/2022.wnut-1.23.pdf"]}
+{"year":"2022","title":"Towards Controllable Protein design with Conditional Transformers","authors":["N Ferruz, B Höcker - arXiv preprint arXiv:2201.07338, 2022"],"snippet":"The 21st century is presenting humankind with unprecedented environmental and medical challenges. The ability to design novel proteins tailored for specific purposes could transform our ability to respond timely to these issues. Recent …","url":["https://arxiv.org/pdf/2201.07338"]}
+{"year":"2022","title":"Towards fairness AI: A data-centric approach","authors":["U Ojha - 2022"],"snippet":"Title: Towards fairness AI: A data-centric approach Subtitle: Assessment and mitigation techniques to tackle bias in datasets The consequences of bias and injustice have received more attention, even though AI is increasingly employed in …","url":["https://webthesis.biblio.polito.it/secure/24666/1/tesi.pdf"]}
+{"year":"2022","title":"Towards Fine (r)-grained Identification of Event Coreference Resolution Types","authors":["L De Langhe, O De Clercq, V Hoste - Computational Linguistics in the Netherlands …, 2022"],"snippet":"… RobBERT on the other hand was pretrained on 6.6B tokens of Commoncrawl webdata (Suárez et al. 2019). Since the Commoncrawl data consists of individual lines and not every line contains more than one sentence, we anticipate that this …","url":["https://www.clinjournal.org/clinj/article/download/154/162"]}
+{"year":"2022","title":"Towards Latvian WordNet","authors":["P Paikens, M Grasmanis, A Klints, I Lokmane…"],"snippet":"In this paper we describe our current work on creating a WordNet for Latvian based on the principles of the Princeton WordNet. The chosen methodology for word sense definition and sense linking is based on corpus evidence and the existing Tezaurs …","url":["https://wordnet.ailab.lv/data/documents/2022/LREC_WordNet.pdf"]}
+{"year":"2022","title":"Towards Lithuanian grammatical error correction","authors":["L Stankevičius, M Lukoševičius - arXiv preprint arXiv:2203.09963, 2022"],"snippet":"Everyone wants to write beautiful and correct text, yet the lack of language skills, experience, or hasty typing can result in errors. By employing the recent advances in transformer architectures, we construct a grammatical error correction model for …","url":["https://arxiv.org/pdf/2203.09963"]}
+{"year":"2022","title":"Towards Multi-Lingual Visual Question Answering","authors":["S Changpinyo, L Xue, I Szpektor, AV Thapliyal… - arXiv preprint arXiv …, 2022"],"snippet":"Visual Question Answering (VQA) has been primarily studied through the lens of the English language. Yet, tackling VQA in other languages in the same manner would require considerable amount of resources. In this paper, we propose scalable …","url":["https://arxiv.org/pdf/2209.05401"]}
+{"year":"2022","title":"Towards Performance of NLP Transformers on URL-Based Phishing Detection for Mobile Devices","authors":["H Shirazia, K Haynesb, I Raya - 2022"],"snippet":"… , and the legitimate webpage sources are Alexa and CommonCrawl.org. In 2020, Shirazi et al. … .com and 10,955 legitimate URLs from CommonCrawl.org. The phishing URLs include sites … Since the CommonCrawl.org corpus contains …","url":["https://iasks.org/articles/juspn-v17-i1-pp-35-42.pdf"]}
+{"year":"2022","title":"Towards Simple and Efficient Task-Adaptive Pre-training for Text Classification","authors":["A Ladkat, A Miyajiwala, S Jagadale, R Kulkarni… - arXiv preprint arXiv …, 2022"],"snippet":"Language models are pre-trained using large corpora of generic data like book corpus, common crawl and Wikipedia, which is essential for the model to understand the linguistic characteristics of the language. New studies suggest using Domain …","url":["https://arxiv.org/pdf/2209.12943"]}
+{"year":"2022","title":"Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning","authors":["A Siddhant, A Bapna, O Firat, Y Cao, MX Chen… - arXiv preprint arXiv …, 2022"],"snippet":"Achieving universal translation between all human language pairs is the holy-grail of machine translation (MT) research. While recent progress in massively multilingual MT is one step closer to reaching this goal, it is becoming evident that …","url":["https://arxiv.org/pdf/2201.03110"]}
+{"year":"2022","title":"Towards Trustworthy AutoGrading of Short, Multi-lingual, Multi-type Answers","authors":["J Schneider, R Richner, M Riser"],"snippet":"Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading …","url":["https://www.researchgate.net/profile/Johannes-Schneider-5/publication/357514804_Towards_Trustworthy_AutoGrading_of_Short_Multi-lingual_Multi-type_Answers/links/61d19825b6b5667157c0640f/Towards-Trustworthy-AutoGrading-of-Short-Multi-lingual-Multi-type-Answers.pdf"]}
+{"year":"2022","title":"Towards Understanding and Practices of Ethical Artificial Intelligence","authors":["J Chi - 2022"],"snippet":"The successes of machine learning (ML) and artificial intelligence (AI) models encourage their widespread deployments in high-stakes domains--from public transportation to social decision-making such as autonomous driving, criminal justice …","url":["https://search.proquest.com/openview/10119af5960676393b0db80567014b74/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
+{"year":"2022","title":"Toxicity Detection for Indic Multilingual Social Media Content","authors":["M Jhaveri, D Ramaiya, HS Chadha - arXiv preprint arXiv:2201.00598, 2022"],"snippet":"… • XLM-RoBERTa - It is a transformer-based masked language model trained on 100 languages, using more than two terabytes of filtered CommonCrawl data. [3] • MuRIL - A multilingual language model specifically built for Indic languages trained …","url":["https://arxiv.org/pdf/2201.00598"]}
+{"year":"2022","title":"Toxicity detection in online Georgian discussions","authors":["N Lashkarashvili, M Tsintsadze - … Journal of Information Management Data Insights, 2022"],"snippet":"… They trained models using Wikipedia and Common Crawl dataset. They used character n-grams with a size equal to 5 and the dimension of embeddings was set to 300. We found that 8,385, about 1 / 4 of the total of 38,733 raw unique words were …","url":["https://www.sciencedirect.com/science/article/pii/S2667096822000064"]}
+{"year":"2022","title":"Tradeoff Options for Bipartite Graph Partitioning","authors":["J Mackenzie, M Petri, A Moffat - IEEE Transactions on Knowledge and Data …, 2022","JMMPA Moffat"],"snippet":"… CC-News-En: A snapshot of English news documents from the Common Crawl between 2016 and 2018 [32]. As was also the case with other work on reordering of inverted indexes, short postings lists (fewer than 4096 elements) and long postings …","url":["https://ieeexplore.ieee.org/abstract/document/9900428/","https://jmmackenzie.io/pdf/mpm22-tkde.pdf"]}
+{"year":"2022","title":"Traditional Machine Learning and Deep Learning-based Text Classification for Turkish Law Documents using Transformers and Domain Adaptation","authors":["O Akça, G Bayrak, AM Issifu, MC Ganіz - … on INnovations in Intelligent SysTems and …, 2022"],"snippet":"… We use their models which are pre-trained on a general common crawl corpus in Turkish. We than fine-tune this general domain model using our corpus that consists of a collection of Turkish legal texts to leverage the power of transfer learning. For …","url":["https://ieeexplore.ieee.org/abstract/document/9894051/"]}
+{"year":"2022","title":"Trainability and real-world knowledge","authors":["A Kornai - Vector Semantics, 2023"],"snippet":"Until this point, we concentrated on the lexicon, conceived of as the repository of shared linguistic information. In 8.1 we take on the problem of integrating real-world knowledge, nowadays typically stored in knowledge graphs as billions of RDF triples …","url":["https://link.springer.com/content/pdf/10.1007/978-981-19-5607-2_8.pdf"]}
+{"year":"2022","title":"Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model …","authors":["PF Chen, TL He, SC Lin, YC Chu, CT Kuo, F Lai… - JMIR Medical Informatics, 2022"],"snippet":"Background: The automatic coding of clinical text documents by using the International Classification of Diseases, 10th Revision (ICD-10) can be performed for statistical analyses and reimbursements. With the development of natural …","url":["https://medinform.jmir.org/2022/11/e41342/"]}
+{"year":"2022","title":"Training a T5 Using Lab-sized Resources","authors":["MR Ciosici, L Derczynski - arXiv preprint arXiv:2208.12097, 2022"],"snippet":"Training large neural language models on large datasets is resourceand time-intensive. These requirements create a barrier to entry, where those with fewer resources cannot build competitive models. This paper presents various techniques for making …","url":["https://arxiv.org/pdf/2208.12097"]}
+{"year":"2022","title":"Training language models for deeper understanding improves brain alignment","authors":["KL Aw, M Toneva - arXiv preprint arXiv:2212.10898, 2022"],"snippet":"… sentences on the C4 dataset, a collection of roughly 750 GB of English texts sourced from the public Common Crawl open repository. … , a collection of roughly 750 GB of English texts sourced from the public Common Crawl open repository …","url":["https://arxiv.org/pdf/2212.10898"]}
+{"year":"2022","title":"TRANS-KBLSTM: An External Knowledge Enhanced Transformer BiLSTM model for Tabular Reasoning","authors":["Y Varun, A Sharma, V Gupta"],"snippet":"Natural language inference on tabular data is a challenging task. Existing approaches lack the world and common sense knowledge required to perform at a human level. While massive amounts of KG data exist, approaches to integrate them …","url":["https://vgupta123.github.io/docs/TransKBLSTM.pdf"]}
+{"year":"2022","title":"Transcormer: Transformer for Sentence Scoring with Sliding Language Modeling","authors":["K Song, Y Leng, X Tan, Y Zou, T Qin, D Li - arXiv preprint arXiv:2205.12986, 2022"],"snippet":"… WMT14 English-German comprises 4.5M bilingual data collected from Europarl v7, Common Crawl corpus and News Commentary. We concatenate newstest2012 and newstest2013 as the valid set, and choose newstest2014 as the test set for WMT14 …","url":["https://arxiv.org/pdf/2205.12986"]}
+{"year":"2022","title":"Transfer Effects in Scandinavian Languages","authors":["A Fredriksen - 2022"],"snippet":"The field of natural language processing with machine learning has gone through a quantum leap in the past decade. Giants like Google and Amazon have paved the way for powerful models trained on a vast amount of data. Even though the …","url":["https://www.duo.uio.no/bitstream/handle/10852/97679/1/AnetteFredriksenThesis.pdf"]}
+{"year":"2022","title":"Transfer language selection for zero-shot cross-lingual abusive language detection","authors":["J Eronen, M Ptaszynski, F Masui, M Arata, G Leliwa… - Information Processing & …, 2022"],"snippet":"We study the selection of transfer languages for automatic abusive language detection. Instead of preparing a dataset for every language, we demonstrate the effectiveness of cross-lingual transfer learning for zero-shot abusive language …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322000978"]}
+{"year":"2022","title":"Transfer Learning Approach to Prediction of Rate of Penetration in Drilling","authors":["A Ambrus, T Wiktorski","FJ Pacis, S Alyaev, A Ambrus, T Wiktorski - International Conference on …, 2022"],"snippet":"The rate of penetration (ROP) is a key performance indicator in the oil and gas drilling industry as it directly translates to cost savings and emission reductions. A prerequisite for a drilling optimization algorithm is a predictive model that provides …","url":["https://link.springer.com/chapter/10.1007/978-3-031-08754-7_44","https://www.iccs-meeting.org/archive/iccs2022/papers/133510330.pdf"]}
+{"year":"2022","title":"Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models","authors":["S Nair, E Yang, D Lawrie, K Duh, P McNamee… - arXiv preprint arXiv …, 2022"],"snippet":"… We also conducted experiments using the new CLIR Common Crawl Collection (HC4) [14], where the documents are newswire articles from Common Crawl in Chinese or Persian. Throughout, English queries are used to search a collection in a non-English …","url":["https://arxiv.org/pdf/2201.08471"]}
+{"year":"2022","title":"Transfer Learning for Automatic Sexism Detection with Multilingual Transformer Models","authors":["D Liakhovets, M Schütz, J Böck, M Andresel… - 2022"],"snippet":"… • XLM-R is also a multilingual model and, similarly to mBERT, is trained on 100 languages with a dataset containing CommonCrawl data. The architecture consists of a combination of the XLM [24] and RoBERTa [25] transformer models. The latter is …","url":["http://ceur-ws.org/Vol-3202/exist-paper1.pdf"]}
+{"year":"2022","title":"Transfer Learning in Natural Language Processing through Interactive Feedback","authors":["M Yuan - 2022"],"snippet":"Machine learning models cannot easily adapt to new domains and applications. This drawback becomes detrimental for natural language processing (NLP) because language is perpetually changing. Across disciplines and languages, there are …","url":["https://drum.lib.umd.edu/bitstream/handle/1903/29333/Yuan_umd_0117E_22783.pdf?sequence=2"]}
+{"year":"2022","title":"Transfer Learning of Transformers for Spoken Language Understanding","authors":["J Švec, A Frémund, M Bulín, J Lehečka - … Conference on Text, Speech, and Dialogue, 2022"],"snippet":"… For the Czech language, we have collected the CommonCrawl corpus at the end of August 2020. It contains 47.9 GB of clean text, 20.5 M unique URLs and 6.7 B running words. The Czech T5 training procedure followed the original procedure …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_40"]}
+{"year":"2022","title":"Transformer Language Models without Positional Encodings Still Learn Positional Information","authors":["A Haviv, O Ram, O Press, P Izsak, O Levy - arXiv preprint arXiv:2203.16634, 2022"],"snippet":"Transformers typically require some form of positional encoding, such as positional embeddings, to process natural language sequences. Surprisingly, we find that transformer language models without any explicit positional encoding are still …","url":["https://arxiv.org/pdf/2203.16634"]}
+{"year":"2022","title":"Transformer models used for text-based question answering systems","authors":["K Nassiri, M Akhloufi - Applied Intelligence, 2022"],"snippet":"The question answering system is frequently applied in the area of natural language processing (NLP) because of the wide variety of applications. It consists of answering questions using natural language. The problem is, in general, solved by …","url":["https://link.springer.com/article/10.1007/s10489-022-04052-8"]}
+{"year":"2022","title":"Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages","authors":["IS Blekanov, N Tarasov, SS Bodrunova - Future Internet, 2022"],"snippet":"… One of the major contributions of the T5 model’s authors was the process of collecting and preprocessing data based on the CommonCrawl initial dataset. As a result of multiple steps of processing, including duplicate, stopwords, and special …","url":["https://www.mdpi.com/1999-5903/14/3/69/pdf"]}
+{"year":"2022","title":"Translation between Molecules and Natural Language","authors":["C Edwards, T Lai, K Ros, G Honke, H Ji - arXiv preprint arXiv:2204.11817, 2022"],"snippet":"Joint representations between images and text have been deeply investigated in the literature. In computer vision, the benefits of incorporating natural language have become clear for enabling semantic-level control of images. In this work, we present …","url":["https://arxiv.org/pdf/2204.11817"]}
+{"year":"2022","title":"Tree-based Search Graph for Approximate Nearest Neighbor Search","authors":["X Fan, X Wang, K Lu, L Xue, J Zhao - arXiv preprint arXiv:2201.03237, 2022"],"snippet":"Nearest neighbor search supports important applications in many domains, such as database, machine learning, computer vision. Since the computational cost for accurate search is too high, the community turned to the research of approximate …","url":["https://arxiv.org/pdf/2201.03237"]}
+{"year":"2022","title":"TrollsWithOpinion: A taxonomy and dataset for predicting domain-specific opinion manipulation in troll memes","authors":["S Suryawanshi, BR Chakravarthi, M Arcan, P Buitelaar - Multimedia Tools and …, 2022"],"snippet":"Memes have become a de-facto media device in online communication. Unfortunately, memes are also used for trolling, which intends to demean, harass, or bully targeted individuals. As a result of which, the targeted individual could fall prey …","url":["https://link.springer.com/article/10.1007/s11042-022-13796-x"]}
+{"year":"2022","title":"Trustworthiness of Health-Related Information on Arabic Social Media","authors":["Y Albalawi"],"snippet":"Social media (SM) platforms play a vital role in disseminating health-related information. However, evidence suggests that Twitter posts (ie, tweets) are often inaccurate; for example, research from Saudi Arabia indicates that 50% of health-related …","url":["https://researchrepository.ul.ie/articles/thesis/Trustworthiness_of_health-related_information_on_Arabic_social_media/21666269/1/files/38408135.pdf"]}
+{"year":"2022","title":"TSMind: Alibaba and Soochow University's Submission to the WMT22 Translation Suggestion Task","authors":["X Ge, K Wang, J Wang, N Xiao, X Duan, Y Zhao… - arXiv preprint arXiv …, 2022"],"snippet":"This paper describes the joint submission of Alibaba and Soochow University, TSMind, to the WMT 2022 Shared Task on Translation Suggestion (TS). We participate in the English-German and English-Chinese tasks. Basically, we utilize …","url":["https://arxiv.org/pdf/2211.08987"]}
+{"year":"2022","title":"Tune in: The afrl wmt21 news-translation systems","authors":["G Erdmann, J Gwinnup, T Anderson - Proceedings of the Sixth Conference on …, 2021"],"snippet":"… The corpus used for the initial model consisted of commoncrawl, paracrawl v1, and newscommentary-v13 from wmt19 and was processed … Dirt cheap web-scale parallel text from the common crawl. In Proceedings of the 51st Annual Meeting of …","url":["https://aclanthology.org/2021.wmt-1.5.pdf"]}
+{"year":"2022","title":"Turkish abstractive text summarization using pretrained sequence-to-sequence models","authors":["B Baykara, T Güngör - Natural Language Engineering, 2022"],"snippet":"The tremendous amount of increase in the number of documents available on the Web has turned finding the relevant piece of information into a challenging, tedious, and time-consuming activity. Accordingly, automatic text summarization has become …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/turkish-abstractive-text-summarization-using-pretrained-sequencetosequence-models/B2A0C3F5A7EE2A4AA2844B3AD3A66748"]}
+{"year":"2022","title":"TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks","authors":["R Hu, D Zhang, D Tao, T Hartvigsen, H Feng… - arXiv preprint arXiv …, 2022"],"snippet":"Foodborne illness is a serious but preventable public health problem -- with delays in detecting the associated outbreaks resulting in productivity loss, expensive recalls, public safety hazards, and even loss of life. While social media is a promising source …","url":["https://arxiv.org/pdf/2205.10726"]}
+{"year":"2022","title":"TweetNLP: Cutting-Edge Natural Language Processing for Social Media","authors":["J Camacho-Collados, K Rezaee, T Riahi, A Ushio… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper we present TweetNLP, an integrated platform for Natural Language Processing (NLP) in social media. TweetNLP supports a diverse set of NLP tasks, including generic focus areas such as sentiment analysis and named entity …","url":["https://arxiv.org/pdf/2206.14774"]}
+{"year":"2022","title":"TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations","authors":["X Zhang, Y Malkov, O Florez, S Park, B McWilliams… - arXiv preprint arXiv …, 2022"],"snippet":"We present TwHIN-BERT, a multilingual language model trained on in-domain data from the popular social network Twitter. TwHIN-BERT differs from prior pre-trained language models as it is trained with not only text-based self-supervision, but also …","url":["https://arxiv.org/pdf/2209.07562"]}
+{"year":"2022","title":"Two-Stream Network for Sign Language Recognition and Translation","authors":["Y Chen, R Zuo, F Wei, Y Wu, S Liu, B Mak - arXiv preprint arXiv:2211.01367, 2022"],"snippet":"Sign languages are visual languages using manual articulations and non-manual elements to convey information. For sign language recognition and translation, the majority of existing approaches directly encode RGB videos into hidden …","url":["https://arxiv.org/pdf/2211.01367"]}
+{"year":"2022","title":"Uncertainty Estimation for Language Reward Models","authors":["A Gleave, G Irving - arXiv preprint arXiv:2203.07472, 2022"],"snippet":"Language models can learn a range of capabilities from unsupervised training on text corpora. However, to solve a particular problem (such as text summarization) it is typically necessary to fine-tune them on a task-specific dataset. It is often easier for …","url":["https://arxiv.org/pdf/2203.07472"]}
+{"year":"2022","title":"Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels","authors":["S Lei, X Zhang, J He, F Chen, CT Lu - Findings of the Association for Computational …, 2022"],"snippet":"… 2020) improves over mBERT by training longer with more data from CommonCrawl, and without the NSP objective. Recently, two self-learning based methods were proposed for cross-lingual transfer. Dong and de Melo …","url":["https://aclanthology.org/2022.findings-naacl.153.pdf"]}
+{"year":"2022","title":"Understanding HTML with Large Language Models","authors":["I Gur, O Nachum, Y Miao, M Safdari, A Huang… - arXiv preprint arXiv …, 2022"],"snippet":"… For this task, we derive a dataset from CommonCrawlCommonCrawl does not include renderings or annotations that would reveal what text in the HTML is associated with which elements. Instead, we infer descriptions of various elements …","url":["https://arxiv.org/pdf/2210.03945"]}
+{"year":"2022","title":"UniCon: Unidirectional Split Learning with Contrastive Loss for Visual Question Answering","authors":["Y Sun, H Ochiai - arXiv preprint arXiv:2208.11435, 2022"],"snippet":"Visual question answering (VQA) that leverages multi-modality data has attracted intensive interest in real-life applications, such as home robots and clinic diagnoses. Nevertheless, one of the challenges is to design robust learning for different client …","url":["https://arxiv.org/pdf/2208.11435"]}
+{"year":"2022","title":"Unified Pretraining Framework for Document Understanding","authors":["J Gu, J Kuen, VI Morariu, H Zhao, N Barmpalios, R Jain… - arXiv preprint arXiv …, 2022"],"snippet":"Document intelligence automates the extraction of information from documents and supports many business applications. Recent self-supervised learning methods on large-scale unlabeled document datasets have opened up promising directions …","url":["https://arxiv.org/pdf/2204.10939"]}
+{"year":"2022","title":"Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks","authors":["J Lu, C Clark, R Zellers, R Mottaghi, A Kembhavi - arXiv preprint arXiv:2206.08916, 2022"],"snippet":"We propose Unified-IO, a model that performs a large variety of AI tasks spanning classical computer vision tasks, including pose estimation, object detection, depth estimation and image generation, vision-and-language tasks such as region …","url":["https://arxiv.org/pdf/2206.08916"]}
+{"year":"2022","title":"Universal Conditional Masked Language Pre-training for Neural Machine Translation","authors":["P Li, L Li, M Zhang, M Wu, Q Liu - arXiv preprint arXiv:2203.09210, 2022"],"snippet":"Pre-trained sequence-to-sequence models have significantly improved Neural Machine Translation (NMT). Different from prior works where pre-trained models usually adopt an unidirectional decoder, this paper demonstrates that pre-training a …","url":["https://arxiv.org/pdf/2203.09210"]}
+{"year":"2022","title":"UNLT: Urdu Natural Language Toolkit","authors":["J Shafi, HR Iqbal, RMA Nawab, P Rayson - Natural Language Engineering, 2022"],"snippet":"This study describes a Natural Language Processing (NLP) toolkit, as the first contribution of a larger project, for an under-resourced language—Urdu. In previous studies, standard NLP toolkits have been developed for English and many other …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/unlt-urdu-natural-language-toolkit/66306F671F7CB1056A004F1A166E8E30"]}
+{"year":"2022","title":"Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval","authors":["N Wu, Y Liang, H Ren, L Shou, N Duan, M Gong… - arXiv preprint arXiv …, 2022"],"snippet":"Recent research demonstrates the effectiveness of using pretrained language models (PLM) to improve dense retrieval and multilingual dense retrieval. In this work, we present a simple but effective monolingual pretraining task called …","url":["https://arxiv.org/pdf/2206.03281"]}
+{"year":"2022","title":"Unsupervised Dense Retrieval Deserves Better Positive Pairs: Scalable Augmentation with Query Extraction and Generation","authors":["R Meng, Y Liu, S Yavuz, D Agarwal, L Tu, N Yu… - arXiv preprint arXiv …, 2022"],"snippet":"… In this section, we introduce several data argumentation methods to create pseudo queries given a document (eg, a passage from a Wikipedia article or a web document from CommonCrawl), without using any annotated queries or questions …","url":["https://arxiv.org/pdf/2212.08841"]}
+{"year":"2022","title":"Unsupervised Extreme Multi Label Classification of Stack Overflow Posts","authors":["P Devine, K Blincoe - 2022"],"snippet":"Knowing the topics of a software forum post, such as those on StackOverflow, allows for greater analysis and understanding of the large amounts of data that come from these communities. One approach to this problem is using extreme multi label …","url":["https://kblincoe.github.io/publications/2022_NLBSE_StackOverflow.pdf"]}
+{"year":"2022","title":"Unsupervised Sentence Textual Similarity with Compositional Phrase Semantics","authors":["Z Wang, J Dou, Y Zhang - arXiv preprint arXiv:2210.02284, 2022"],"snippet":"… 2014): We use the 300D GloVe vectors trained on Common Crawl (840B tokens, 2.2M vocabulary) 15. • fastText (Bojanowski et al.… 2017): We use the 300D fastText vectors trained on Common Crawl (600B tokens) without subword information 16. …","url":["https://web7.arxiv.org/pdf/2210.02284"]}
+{"year":"2022","title":"Unsupervised Visual Domain Adaptation by Self-Guided Learning","authors":["J Gao - 2022"],"snippet":"… video action understanding Common Crawl 2020 … In the field of natural language processing, the training datasets used by the leading model GPT-3 [16] include the 410 billion token Common Crawl archive 1 and 86 billion tokens from …","url":["https://pure.qub.ac.uk/files/381689911/corrected_thesis_jian_1107_v3.pdf"]}
+{"year":"2022","title":"UoR-NCL at SemEval-2022 Task 3: Fine-Tuning the BERT-Based Models for Validating Taxonomic Relations","authors":["T Markchom, H Liang, J Chen - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"In human languages, there are many presuppositional constructions that impose a constrain on the taxonomic relations between two nouns depending on their order. These constructions create a challenge in validating taxonomic relations in real-world …","url":["https://aclanthology.org/2022.semeval-1.33.pdf"]}
+{"year":"2022","title":"UPV at TREC Health Misinformation Track 2021","authors":["IB Schlicht, AFM de Paula, P Rosso"],"snippet":"Health misinformation on search engines is a significant problem that could negatively affect individuals or public health. To mitigate the problem, TREC organizes a health misinformation track. This paper presents our submissions to this …","url":["https://trec.nist.gov/pubs/trec30/papers/UPV-HM.pdf"]}
+{"year":"2022","title":"Use the Metadata, Luke!–An Experimental Joint Metadata Search and N-gram Trend Viewer for Personal Web Archives","authors":["B Indig, Z Sárközi-Lindner, M Nagy - Proceedings of the 2nd International Workshop …, 2022"],"snippet":"… This puts pressure on website operators, as everyone is forced to create an archive of their own, the very issue that was intended to be avoided by shared archives such as Common Crawl that have become trapped in a rivalry of quantity …","url":["https://aclanthology.org/2022.nlp4dh-1.7.pdf"]}
+{"year":"2022","title":"Using a Pre-trained SimpleT5 Model for Text Simplification in a limited Corpus","authors":["J Monteiro, M Aguiar, S Araújo - Proceedings of the Working Notes of CLEF, 2022"],"snippet":"In this paper, we describe our approach for solving Task 3 of the SimpleText Lab, organized as part of the Clef 2022 conference. The SimpleText Lab addresses issues of automatic text simplification of scientific texts in order to make scientific …","url":["http://ceur-ws.org/Vol-3180/paper-241.pdf"]}
+{"year":"2022","title":"Using Context-Free Grammar to Generate Synthetic Technical Short Texts","authors":["T Bikaun, M Stewart, M Hodkiewicz - Australasian Joint Conference on Artificial …, 2022"],"snippet":"… Pre-trained language models take advantage of hundreds of millions of open-domain training examples derived from sources such as the English Wikipedia, Toronto BookCorpus, and Common Crawl Corpus to learn powerful representations over …","url":["https://link.springer.com/chapter/10.1007/978-3-031-22695-3_23"]}
+{"year":"2022","title":"Using Contextual Information to Process Out-of-Vocabulary Words in Spoken Dialog Systems","authors":["A Horndasch - 2022"],"snippet":"Speech is a very efficient channel for communication, but it is a challenge to cope with words which are unknown to one of the dialogue partners. Human beings are very good at dealing with words that are not in their vocabulary, for example by …","url":["https://opus4.kobv.de/opus4-fau/files/20700/AxelHorndaschDissertation.pdf"]}
+{"year":"2022","title":"Using Deep Learning Techniques, A Framework for Estimating the Nutritional Value of Food in Real TIME","authors":["S Bahadur, R Kushwaha, S Sharma, SG Anuradha - International Journal of Health Sciences"],"snippet":"… The HTML format is used to store the raw text data acquired from Google and Common Crawl. HTML tags, CSS, JavaScript code, and comments have been removed during the preprocessing process. To extract individual words, such meta-data …","url":["https://www.neliti.com/publications/430147/using-deep-learning-techniques-a-framework-for-estimating-the-nutritional-value"]}
+{"year":"2022","title":"Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model","authors":["S Smith, M Patwary, B Norick, P LeGresley… - arXiv preprint arXiv …, 2022"],"snippet":"… Other Datasets: In addition to Common Crawl data, we leveraged a number of other previously generated datasets. From The Pile, we … To compound this issue, the URLs scraped in different Common Crawl snapshots are not necessarily unique …","url":["https://arxiv.org/pdf/2201.11990"]}
+{"year":"2022","title":"Using distributional thesaurus to enhance transformer-based contextualized representations for low resource languages","authors":["G Venkatesh, A Jana, S Remus, Ö Sevgili… - Proceedings of the 37th …, 2022"],"snippet":"… XLM-RoBERTa [8] is a large multilingual model, based on the RoBERTa architecture, pretrained on 2.5TB of filtered CommonCrawl data. Experiments confirm that it outperforms mBERT on a wide range of cross-lingual tasks. Alongside …","url":["https://dl.acm.org/doi/abs/10.1145/3477314.3507077"]}
+{"year":"2022","title":"Using Emotion Embeddings to Transfer Knowledge Between Emotions, Languages, and Annotation Formats","authors":["G Chochlakis, G Mahajan, S Baruah, K Burghardt… - arXiv preprint arXiv …, 2022"],"snippet":"… It decreases α to 0.3 and switches to the CommonCrawl dataset, which has a more balanced language distribution. It also disposes of language embeddings and TLM. XLM-T [2] extends XLM-R by finetuning it on tweets to perform multilingual …","url":["https://arxiv.org/pdf/2211.00171"]}
+{"year":"2022","title":"Using Information-Seeking Argument Mining to Improve Service","authors":["B Skiera, S Yan, J Daxenberger, M Dombois… - Journal of Service Research, 2022"],"snippet":"If service providers can identify reasons users are in favor of or against a service, they have insightful information that can help them understand user behavior and what they need to do to change such behavior. This article argues that the novel text-mining …","url":["https://journals.sagepub.com/doi/pdf/10.1177/10946705221110845"]}
+{"year":"2022","title":"Using Informative Data Subsets for Efficient Training of Large Language Models: An Initial Study","authors":["HK Renduchintala, K Killamsetty, S Bhatia, M Aggarwal…"],"snippet":"Abstract Language Models (LMs) are pretrained on large unlabeled corpora through selfsupervision tasks and have become ubiquitous to several NLP applications. Recent trends indicate that the generalization capability of Large LMs (LLMs) …","url":["http://sumitbhatia.net/papers/ingenious-enlsp.pdf"]}
+{"year":"2022","title":"Using Keyqueries to Reduce Misinformation in Health-Related Search Results","authors":["M Fröbe, S Günther, A Bondarenko, J Huck, M Hagen - 2022"],"snippet":"In the scenario of health-related searches, we investigate whether explicit relevance feedback by experts can guide query expansion methods to formulate queries that return fewer misleading or wrong results. In contrast to standard query expansion …","url":["https://webis.de/downloads/publications/papers/froebe_2022c.pdf"]}
+{"year":"2022","title":"Using Natural Language Processing Techniques to Improve Manual Test Case Descriptions","authors":["M Viggiato, D Paas, C Buzon, CP Bezemer"],"snippet":"Despite the recent advancements in test automation, software testing often remains a manual, and costly, activity in many industries. Manual test cases, often described only in natural language, consist of one or more test steps, which are instructions …","url":["http://asgaard.ece.ualberta.ca/papers/Conference/ICSE-SEIP_2022_Viggiato_Using_Natural_Language_Processing_Techniques_to_Improve_Manual_Test_Case_Descriptions.pdf"]}
+{"year":"2022","title":"Using Transformer models for gender attribution in Polish","authors":["K Kaczmarek, J Pokrywka, F Graliński - 2022 17th Conference on Computer Science …, 2022"],"snippet":"… We searched the contents of CommonCrawl 2019 (as provided to us by the authors of [6]2) for the six-gram fragments of the HSSS test set, obviously taking into account the fact that feminine gender-specific forms were modified during the …","url":["https://ieeexplore.ieee.org/abstract/document/9908765/"]}
+{"year":"2022","title":"Utilizing Deep Learning for Detecting Adverse Drug Events in Structured and Unstructured Regulatory Drug Data Sets","authors":["BM Knisely, Q Hatim, M Vaughn-Cooke - Pharmaceutical Medicine, 2022"],"snippet":"Background The US Food and Drug Administration (FDA) collects and retains several data sets on post-market drugs and associated adverse events (AEs). The FDA Adverse Event Reporting System (FAERS) contains millions of AE reports …","url":["https://link.springer.com/article/10.1007/s40290-022-00434-y"]}
+{"year":"2022","title":"Utilizing subjectivity level to mitigate identity term bias in toxic comments classification","authors":["Z Zhao, Z Zhang, F Hopfgartner - Online Social Networks and Media, 2022"],"snippet":"Toxic comment classification models are often found biased towards identity terms, ie, terms characterizing a specific group of people such as “Muslim” and “black”. Such bias is commonly reflected in false positive predictions, ie, non-toxic comments with …","url":["https://www.sciencedirect.com/science/article/pii/S246869642200009X"]}
+{"year":"2022","title":"UTSA NLP at SemEval-2022 Task 4: An Exploration of Simple Ensembles of Transformers, Convolutional, and Recurrent Neural Networks","authors":["X Zhao, A Rios - arXiv preprint arXiv:2203.14920, 2022"],"snippet":"The act of appearing kind or helpful via the use of but having a feeling of superiority condescending and patronizing language can have have serious mental health implications to those that experience it. Thus, detecting this condescending and …","url":["https://arxiv.org/pdf/2203.14920"]}
+{"year":"2022","title":"UWaterlooMDS at the TREC 2021 Health Misinformation Track","authors":["M ABUALSAUD, IX CHEN, K GHAJAR, LNHI PHAN…"],"snippet":"… Using the hosts in M as a base, we expanded this list using the common crawl host graph 8. The hosts graph contains roughly 4 million nodes … We do this by calculating PageRank scores in a subset of the common crawl host-level graph. The …","url":["https://trec.nist.gov/pubs/trec30/papers/UwaterlooMDS-HM.pdf"]}
+{"year":"2022","title":"Vega-MT: The JD Explore Academy Translation System for WMT22","authors":["C Zan, K Peng, L Ding, B Qiu, B Liu, S He, Q Lu… - arXiv preprint arXiv …, 2022","C Zanℜ, K Peng, L Dingℜ, B Qiu, B Liu, S He, Q Lu…"],"snippet":"We describe the JD Explore Academy's submission of the WMT 2022 shared general translation task. We participated in all high-resource tracks and one medium-resource track, including Chinese-English, German-English, Czech-English, Russian-English …","url":["https://arxiv.org/pdf/2209.09444","https://www.statmt.org/wmt22/pdf/2022.wmt-1.37.pdf"]}
+{"year":"2022","title":"Vicomtech at DA-VINCIS: Detection of Aggressive and Violent Incidents from Social Media in Spanish","authors":["P Turón, N Perez, A García-Pablos, E Zotova… - 2022"],"snippet":"This paper describes the participation of the Vicomtech NLP team in the DA-VINCIS shared task. This shared task is focused on mentions of violent events in Spanish tweets, and proposes two subtasks: first, detecting whether a violent incident is …","url":["http://ceur-ws.org/Vol-3202/davincis-paper4.pdf"]}
+{"year":"2022","title":"Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog","authors":["M Hämäläinen, K Alnajjar, T Poibeau - 2022"],"snippet":"We present a method for extracting a multilingual sentiment annotated dialog data set from Fallout New Vegas. The game developers have preannotated every line of dialog in the game in one of the 8 different sentiments: anger, disgust, fear, happy …","url":["https://www.researchgate.net/profile/Mika-Haemaelaeinen/publication/363367422_Video_Games_as_a_Corpus_Sentiment_Analysis_using_Fallout_New_Vegas_Dialog/links/6319cc1870cc936cd3f1ae29/Video-Games-as-a-Corpus-Sentiment-Analysis-using-Fallout-New-Vegas-Dialog.pdf"]}
+{"year":"2022","title":"Vietnamese Hate and Offensive Detection using PhoBERT-CNN and Social Media Streaming Data","authors":["K Quoc Tran, A Trong Nguyen, PG Hoang, CD Luu… - Neural Computing and …, 2022","KQ Tran, AT Nguyen, PG Hoang, CD Luu, TH Do… - arXiv preprint arXiv …, 2022"],"snippet":"… XLM-RoBERTa (XLM-R) [28]: is a multilingual model trained using over two terabytes of cleaned and filtered CommonCrawl data. Upsampling low-resource languages during training and vocabulary generation, generating a more extensive …","url":["https://arxiv.org/pdf/2206.00524","https://link.springer.com/article/10.1007/s00521-022-07745-w"]}
+{"year":"2022","title":"Visualization of 2D fractal structures associated with the Riemann zeta function","authors":["I Belovas, M Sabaliauskas, L Kuzma - DAMSS: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:147807019/147807019.pdf"]}
+{"year":"2022","title":"Visuelle Exploration von indirekten Befangenheiten bei der Verarbeitung natürlicher Sprachen durch Transformer Modelle","authors":["JLAD Petit-Frere"],"snippet":"… Common Crawl corpora are composed of text dataset collected from web pages and contains several billion tokens … This metric was used to measure the biases within the Common Crawl pre-trained GloVe model, an ELMo model, and the bert-base …","url":["https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-thesis.pdf"]}
+{"year":"2022","title":"ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation","authors":["L Phan, H Tran, H Nguyen, TH Trinh - arXiv preprint arXiv:2205.06457, 2022"],"snippet":"We present ViT5, a pretrained Transformer-based encoder-decoder model for the Vietnamese language. With T5-style self-supervised pretraining, ViT5 is trained on a large corpus of high-quality and diverse Vietnamese texts. We benchmark ViT5 on …","url":["https://arxiv.org/pdf/2205.06457"]}
+{"year":"2022","title":"VLT: Vision-Language Transformer and Query Generation for Referring Segmentation","authors":["H Ding, C Liu, S Wang, X Jiang - IEEE Transactions on Pattern Analysis and Machine …, 2022"],"snippet":"We propose a Vision-Language Transformer (VLT) framework for referring segmentation to facilitate deep interactions among multi-modal information and enhance the holistic understanding to vision-language features. There are different …","url":["https://ieeexplore.ieee.org/abstract/document/9932025/"]}
+{"year":"2022","title":"Vocabulary Volume: A New Metric for Assessing Vocabulary Knowledge","authors":["D Tellols, T Tokunaga, H Yokono"],"snippet":"This paper presents Vocabulary Volume, a new metric to assess vocabulary knowledge. The existing metrics for vocabulary knowledge assessment rely on word difficulty, which is often defined in terms of the use frequency of words. In addition to …","url":["https://www.cl.c.titech.ac.jp/tokunaga/_media/publication/csedu_2022_76_cr.pdf"]}
+{"year":"2022","title":"Voices of First Responders—Nationwide Public Safety Communication Survey Findings","authors":["A Pintar, K Buchanan, YY Choong - 2022"],"snippet":"Public safety is in the midst of a major transition in the communication technology that is used due to the ongoing development and deployment of the Nationwide Public Safety Broadband Network (NPSBN). Once established, the NPSBN will …","url":["https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935335"]}
+{"year":"2022","title":"Voicing challenges: GDPR and AI research","authors":["K Quezada-Tavarez, L Dutkiewicz, N Krack - Open Research Europe, 2022"],"snippet":"EU data protection rules could be difficult for researchers to navigate, particularly when processing massive datasets containing personal data for Artificial Intelligence (AI) developments. This article examines how data protection intersects with AI …","url":["https://open-research-europe.ec.europa.eu/articles/2-126"]}
+{"year":"2022","title":"WarpGate: A Semantic Join Discovery System for Cloud Data Warehouses","authors":["T Cong, J Gale, J Frantz, HV Jagadish, Ç Demiralp"],"snippet":"… In the database community, Web table corpora [11, 18] extracted from the Common Crawl contribute the largest publicly accessible relational table datasets. Efforts exploring representation learning for relational tables [8, 17] have trained …","url":["https://www.cidrdb.org/cidr2023/papers/p75-cong.pdf"]}
+{"year":"2022","title":"Web Data Commons-Schema. org Table Annotation Benchmark","authors":["K Korini, R Peeters, C Bizer"],"snippet":"… The Web Data Commons project regularly extracts such data from the Common Crawl and provides it for public download. The Schema.org Table Corpus was created using schema.org data from the December 2020 version of the Web Data …","url":["https://webdatacommons.org/structureddata/sotab/"]}
+{"year":"2022","title":"Web-Based Communication of Wooden Sport Equipment: An Analysis Based on Six Olympic Sports","authors":["F Negro, S Blanc, S Bruzzese, A Falaschi, F Ruffinatto… - Forests, 2022"],"snippet":"Wood has traditionally been used to make sports equipment and playing surfaces. While its use is outdated in several sports, in many others, wood remains well-established or even the material of choice, eg, to make basketball floors or table tennis rackets …","url":["https://www.mdpi.com/1999-4907/13/9/1364/pdf?version=1661587607"]}
+{"year":"2022","title":"Webformer: Pre-training with Web Pages for Information Retrieval","authors":["Y Guo, Z Ma, J Mao, H Qian, X Zhang, H Jiang, Z Cao… - Proceedings of the 45th …, 2022"],"snippet":"Pre-trained language models (PLMs) have achieved great success in the area of Information Retrieval. Studies show that applying these models to ad-hoc document ranking can achieve better retrieval effectiveness. However, on the Web, most …","url":["https://dl.acm.org/doi/abs/10.1145/3477495.3532086"]}
+{"year":"2022","title":"WebFormer: The Web-page Transformer for Structure Information Extraction","authors":["Q Wang, Y Fang, A Ravula, F Feng, X Quan, D Liu - arXiv preprint arXiv:2202.00217, 2022"],"snippet":"… We evaluate WebFormer on SWDE and Common Crawl benchmarks, which shows superior performance over several state-of-the-art methods. The experimental results also demonstrate the effectiveness of WebFormer in modeling …","url":["https://arxiv.org/pdf/2202.00217"]}
+{"year":"2022","title":"Webis at TREC 2021: Deep Learning, Health Misinformation, and Podcasts Tracks","authors":["A Bondarenko, M Fröbe, M Gohsen, S Günther…"],"snippet":"… Mean and PageRank of the domain provided by the Common Crawl,2 as well as six query … up to 1000 anchor texts extracted from six Common Crawl snapshots from the years 2016 to … Here, we use only anchor texts extracted from the …","url":["https://webis.de/downloads/publications/papers/bondarenko_2021f.pdf"]}
+{"year":"2022","title":"WeLM: A Well-Read Pre-trained Language Model for Chinese","authors":["H Su, X Zhou, H Yu, Y Chen, Z Zhu, Y Yu, J Zhou - arXiv preprint arXiv:2209.10372, 2022"],"snippet":"… monthly shards released by Common Crawl to construct a general… common crawl. In Figure 2, we visualize the document length and topic distribution in the training data. Topics are detected with pre-trained topic classification models. We …","url":["https://arxiv.org/pdf/2209.10372"]}
+{"year":"2022","title":"What do Toothbrushes do in the Kitchen? How Transformers Think our World is Structured","authors":["A Henlein, A Mehler - arXiv preprint arXiv:2204.05673, 2022"],"snippet":"Transformer-based models are now predominant in NLP. They outperform approaches based on static models in many respects. This success has in turn prompted research that reveals a number of biases in the language models …","url":["https://arxiv.org/pdf/2204.05673"]}
+{"year":"2022","title":"What is it like to program with artificial intelligence?","authors":["A Sarkar, AD Gordon, C Negreanu, C Poelitz… - arXiv preprint arXiv …, 2022"],"snippet":"… For example, the Common Crawl project1 produces around 20 TB of text data (from web pages) monthly, but labelled task-specific data is less prevalent. This makes unsupervised training appealing which leads to the concept of pre-trained LMs (J. Li …","url":["https://arxiv.org/pdf/2208.06213"]}
+{"year":"2022","title":"What Is Love?: Text Analytics on Romance Literature From the Perspective of Authors","authors":["CH Naing, X Zhao, KH Gan, NH Samsudin - … of Research on Opinion Mining and Text …, 2022"],"snippet":"Descriptions of love can be found in a wide range of literature. The meaning of love that a reader grasps from reading a literary work is mostly the result of self-understanding and is very likely different from the one that the author tried to express. Therefore, it …","url":["https://www.igi-global.com/chapter/what-is-love/298871"]}
+{"year":"2022","title":"What Language Model to Train if You Have One Million GPU Hours?","authors":["T Le Scao, T Wang, D Hesslow, L Saulnier, S Bekman… - Challenges {\\&, 2022"],"snippet":"… crawls with curated highquality sources significantly improves zeroshot generalization over pretraining datasets constructed from Common Crawl only. … First, we have found that complimenting Common Crawl data with high-quality cross-domain …","url":["https://openreview.net/pdf?id=rI7BL3fHIZq"]}
+{"year":"2022","title":"WHAT NEURAL NETWORKS KNOW ABOUT LINGUISTIC COMPLEXITY","authors":["SA Sharoff - Russian Journal of Linguistics, 2022","SS Aleksandrovich - Russian Journal of Linguistics, 2022"],"snippet":"Linguistic complexity is a complex phenomenon, as it manifests itself on different levels (complexity of texts to sentences to words to subword units), through different features (genres to syntax to semantics), and also via different tasks (language …","url":["https://cyberleninka.ru/article/n/what-neural-networks-know-about-linguistic-complexity","https://journals.rudn.ru/linguistics/article/view/31329"]}
+{"year":"2022","title":"What Really Matters? Evaluating the Importance of Skills for Data Analysts","authors":["CA Collier, AL Powell - 2022"],"snippet":"… First, the job postings utilized in Dong and Triche’s study were not comprehensive but rather only those captured by the Common Crawl tool to facilitate the longitudinal nature of their study. Second, the wildcard searches used by Dong and Triche …","url":["https://aisel.aisnet.org/amcis2022/sig_ed/sig_ed/20/"]}
+{"year":"2022","title":"When danger strikes: A linguistic tool for tracking America's collective response to threats","authors":["VK Choi, S Shrestha, X Pan, MJ Gelfand - Proceedings of the National Academy of …, 2022"],"snippet":"In today’s vast digital landscape, people are constantly exposed to threatening language, which attracts attention and activates the human brain’s fear circuitry. However, to date, we have lacked the tools needed to identify threatening language …","url":["https://www.pnas.org/content/pnas/119/4/e2113891119.full.pdf"]}
+{"year":"2022","title":"When Pairs Meet Triplets: Improving Low-Resource Captioning via Multi-Objective Optimization","authors":["Y Wu, S Zhao, Y Zhang, X Yuan, Z Su - ACM Transactions on Multimedia Computing …, 2022"],"snippet":"Image captioning for low-resource languages has attracted much attention recently. Researchers propose to augment the low-resource caption dataset into (image, rich-resource language, and low-resource language) triplets and develop the dual attention …","url":["https://dl.acm.org/doi/abs/10.1145/3492325"]}
+{"year":"2022","title":"Where do I Belong in Six Centuries of Literature?","authors":["J Silva, S Grilo, M Bolrinha, R Santos, L Gomes…"],"snippet":"Enhancing the availability of corpora and processing tools for language research is a central endeavour of the CLARIN research infrastructure. In this chapter we report on how PORTULAN CLARIN, with the support of the national institute for the …","url":["http://www.di.fc.ul.pt/~ahb/pubs/2022SilvaGriloEtAl.pdf"]}
+{"year":"2022","title":"Where Is My Training Bottleneck? Hidden Trade-Offs in Deep Learning Preprocessing Pipelines","authors":["A Isenko, R Mayer, J Jedele, HA Jacobsen - arXiv preprint arXiv:2202.08679, 2022"],"snippet":"Preprocessing pipelines in deep learning aim to provide sufficient data throughput to keep the training processes busy. Maximizing resource utilization is becoming more challenging as the throughput of training processes increases with hardware …","url":["https://arxiv.org/pdf/2202.08679"]}
+{"year":"2022","title":"Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection","authors":["S Gururangan, D Card, SK Drier, EK Gade, LZ Wang… - arXiv preprint arXiv …, 2022"],"snippet":"… Web dumps like Common Crawl offer the promise of more diverse text than what is available in curated resources. However, much of the web consists of frequently replicated boilerplate (eg, privacy policies), code (eg, HTML and Javascript) …","url":["https://arxiv.org/pdf/2201.10474"]}
+{"year":"2022","title":"Why Do Neural Language Models Still Need Commonsense Knowledge to Handle Semantic Variations in Question Answering?","authors":["S Kwon, C Kang, J Han, J Choi - arXiv preprint arXiv:2209.00599, 2022"],"snippet":"… Finally, RoBERTa is pretrained with approximately 160GB of data including the BERT pretraining corpora as well as three additional corpora (CommonCrawl News dataset27, open-source recreation of the WebText corpus28 and STORIES corpus29) …","url":["https://arxiv.org/pdf/2209.00599"]}
+{"year":"2022","title":"Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning","authors":["TT Nguyen, F Trahay, J Domke, A Drozd, E Vatai… - IEEE International Parallel & …, 2022"],"snippet":"Stochastic gradient descent (SGD) is the most prevalent algorithm for training Deep Neural Networks (DNN). SGD iterates the input data set in each training epoch processing data samples in a random access fashion. Because this puts enormous …","url":["https://hal.archives-ouvertes.fr/hal-03599740/document"]}
+{"year":"2022","title":"WikiMulti: a Corpus for Cross-Lingual Summarization","authors":["P Tikhonov, V Malykh - arXiv preprint arXiv:2204.11104, 2022"],"snippet":"Cross-lingual summarization (CLS) is the task to produce a summary in one particular language for a source document in a different language. We introduce WikiMulti - a new dataset for cross-lingual summarization based on Wikipedia …","url":["https://arxiv.org/pdf/2204.11104"]}
+{"year":"2022","title":"Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning","authors":["P Villalobos, J Sevilla, L Heim, T Besiroglu… - arXiv preprint arXiv …, 2022"],"snippet":"… 5) CommonCrawl CommonCrawl releases monthly crawls which for the past four years have contained 5-10TB of compressed plaintext.Half of the URLs in … At 200M words per GB of text, CommonCrawl produces between 8.3e12 and 4.4e13 …","url":["https://arxiv.org/pdf/2211.04325"]}
+{"year":"2022","title":"Within-pair factors might explain the inconsistent effects of animacy on paired-associates recall","authors":["MJ Serra, CM DeYoung - Psychonomic Bulletin & Review, 2022"],"snippet":"The tendency for people to have better memory for animate (living) concepts than inanimate (nonliving) concepts in memory tasks involving free recall and recognition suggests that animacy status can be an important predictor of memory. To date …","url":["https://link.springer.com/article/10.3758/s13423-022-02184-z"]}
+{"year":"2022","title":"Witscript 2: A System for Generating Improvised Jokes Without Wordplay","authors":["J Toplyn"],"snippet":"A previous paper presented Witscript, a system for generating conversational jokes that rely on wordplay. This paper extends that work by presenting Witscript 2, which uses a large language model to generate conversational jokes that rely on common …","url":["https://computationalcreativity.net/iccc22/wp-content/uploads/2022/06/ICCC-2022_3S_Toplyn.pdf"]}
+{"year":"2022","title":"Word Embeddings for Automatic Equalization in Audio Mixing","authors":["S Venkatesh, D Moffat, ER Miranda - arXiv preprint arXiv:2202.08898, 2022"],"snippet":"… It trains on the World Wide Web using Common Crawl, which is a larger corpus of text. Tok2Vec is a word embedding model provided by a company called spaCy [31]. We did not find the entire details regarding its implementation, but the model is …","url":["https://arxiv.org/pdf/2202.08898"]}
+{"year":"2022","title":"Word formation supports efficient communication: The case of compounds","authors":["A Xu, C Kemp, L Frermann, Y Xu"],"snippet":"Compounding is a common type of word formation extensively studied in linguistics and cognitive psychology. A growing line of research suggests that the lexicon supports efficient communication by balancing informativeness and simplicity. We …","url":["http://www.charleskemp.com/papers/xukfx_wordformationsupportsefficientcommunicationthecaseofcompounds.pdf"]}
+{"year":"2022","title":"Work-in-Progress: Computing Sentence Similarity for Short Texts using Transformer models","authors":["V Ramnarain-Seetohul, V Bassoo, Y Rosunally - 2022 IEEE Global Engineering …, 2022"],"snippet":"… The OpenAI GPT-3, an autoregressive language model with 175 billion parameters, is trained with the Common Crawl corpus of data, web text, books, and Wikipedia [10]. The OpenAI offers an API to use the GPT-3 model for registered users …","url":["https://ieeexplore.ieee.org/abstract/document/9766649/"]}
+{"year":"2022","title":"WuDaoMM: A large-scale Multi-Modal Dataset for Pre-training models","authors":["S Yuan, Z Shuai, L Jiahong, X Zhao, Z Hanyu, T Jie - arXiv preprint arXiv:2203.11480, 2022"],"snippet":"… LAION-400M is a larger-scale vision-language corpus, which uses Common Crawl as the data source and applies a series of exquisite data cleaning rules. In contrast, Chinese-based multi-modal datasets are relatively rare and the scale of …","url":["https://arxiv.org/pdf/2203.11480"]}
+{"year":"2022","title":"XDoc: Unified Pre-training for Cross-Format Document Understanding","authors":["J Chen, T Lv, L Cui, C Zhang, F Wei - arXiv preprint arXiv:2210.02849, 2022"],"snippet":"… 2022a), we take advantage of the large-scale dataset Common Crawl3, which contains petabytes of web pages in raw formats. Specifically, text contents and HTML tags are both available for each web page. According to (Li et al., 2022a), the …","url":["https://arxiv.org/pdf/2210.02849"]}
+{"year":"2022","title":"XLCNN: pre-trained transformer model for malware detection","authors":["Κ Γιαπαντζής - 2022"],"snippet":"The present thesis describes a Transformer-based neural network model that was developed in order to detect malicious software. We believe that the scientific community should take advantage of the contribution of Transformer models in the …","url":["https://dspace.lib.uom.gr/bitstream/2159/26452/1/GiapantzisKonstantinosMsc2022.pdf"]}
+{"year":"2022","title":"XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond","authors":["F Barbieri, LE Anke, J Camacho-Collados"],"snippet":"Abstract Language models are ubiquitous in current NLP, and their multilingual capacity has recently attracted considerable attention. However, current analyses have almost exclusively focused on (multilingual variants of) standard benchmarks …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.27.pdf"]}
+{"year":"2022","title":"XTREME-S: Evaluating Cross-lingual Speech Representations","authors":["A Conneau, A Bapna, Y Zhang, M Ma, P von Platen… - arXiv preprint arXiv …, 2022"],"snippet":"We introduce XTREME-S, a new benchmark to evaluate universal cross-lingual speech representations in many languages. XTREME-S covers four task families: speech recognition, classification, speech-to-text translation and retrieval. Covering …","url":["https://arxiv.org/pdf/2203.10752"]}
+{"year":"2022","title":"Ynu-hpcc at semeval-2022 task 2: Representing multilingual idiomaticity based on contrastive learning","authors":["K Liu, J Wang, X Zhang - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"This paper will present the methods we use as the YNU-HPCC team in the SemEval-2022 Task 2, Multilingual Idiomaticity Detection and Sentence Embedding. We are involved in two subtasks, including four settings. In subtask B of sentence …","url":["https://aclanthology.org/2022.semeval-1.26.pdf"]}
+{"year":"2022","title":"You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual Settings","authors":["Z Talat, A Névéol, S Biderman, M Clinciu, M Dey… - Challenges {\\&, 2022"],"snippet":"Evaluating bias, fairness, and social impact in monolingual language models is a difficult task. This challenge is further compounded when language modeling occurs in a multilingual context. Considering the implication of evaluation biases for large …","url":["https://openreview.net/pdf?id=rK-7NhfSIW5"]}
+{"year":"2022","title":"Zero Shot Crosslingual Eye-Tracking Data Prediction using Multilingual Transformer Models","authors":["H Srivastava - 2022"],"snippet":"Eye tracking data during reading is a useful source of information to understand the cognitive processes that take place during language comprehension processes. Different languages account for different brain triggers, however there seems to be …","url":["https://openreview.net/pdf?id=HZxe1KUug5"]}
+{"year":"2022","title":"Zero-shot Commonsense Question Answering with Cloze Translation and Consistency Optimization","authors":["ZY Dou, N Peng - arXiv preprint arXiv:2201.00136, 2022"],"snippet":"… Concretely, first, they create a cloze question corpus by masking noun phrases and named entities in statements sampled from Wikipedia, and a natural question corpus by mining questions containing some common wh-words from CommonCrawl …","url":["https://arxiv.org/pdf/2201.00136"]}
+{"year":"2022","title":"Zero-Shot Ranking Socio-Political Texts with Transformer Language Models to Reduce Close Reading Time","authors":["K Akdemir, A Hürriyetoğlu - arXiv preprint arXiv:2210.09179, 2022"],"snippet":"We approach the classification problem as an entailment problem and apply zero-shot ranking to socio-political texts. Documents that are ranked at the top can be considered positively classified documents and this reduces the close reading time …","url":["https://arxiv.org/pdf/2210.09179"]}
+{"year":"2022","title":"Zhichunroad at semeval-2022 task 2: Adversarial training and contrastive learning for multiword representations","authors":["X Cui, W Xiong, S Wang - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"This paper presents our contribution to the SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding. We explore the impact of three different pre-trained multilingual language models in the SubTaskA. By enhancing …","url":["https://aclanthology.org/2022.semeval-1.24.pdf"]}