Dataset Preview
Full Screen
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type string to null
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in <listcomp>
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2075, in cast_array_to_feature
                  casted_array_values = _c(array.values, feature.feature)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1962, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type string to null
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1524, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1099, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

paper_id
string
conference
string
decision
null
url
null
hasContent
string
hasReview
string
title
string
authors
sequence
ACL_2017_104
ACL
null
null
true
true
Bridging Text and Knowledge by Learning Multi-Prototype Entity Mention Embedding
[]
ACL_2017_105
ACL
null
null
true
true
Morphological Inflection Generation with Hard Monotonic Attention
[]
ACL_2017_107
ACL
null
null
true
true
Weakly Supervised Cross-Lingual Named Entity Recognition via Effective Annotation and Representation Projection
[]
ACL_2017_108
ACL
null
null
true
true
A Multigraph-based Model for Overlapping Entity Recognition
[]
ACL_2017_117
ACL
null
null
true
true
Improved Neural Relation Detection for Knowledge Base Question Answering
[]
ACL_2017_122
ACL
null
null
true
true
Neural Belief Tracker: Data-Driven Dialogue State Tracking
[]
ACL_2017_128
ACL
null
null
true
true
Knowledge as a Teacher: Knowledge-Guided Structural Attention Networks
[]
ACL_2017_12
ACL
null
null
true
true
Time Expression Analysis and Recognition Using Syntactic Types and Simple Heuristic Rules
[]
ACL_2017_130
ACL
null
null
true
true
Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts
[]
ACL_2017_134
ACL
null
null
true
true
Neural End-to-End Learning for Computational Argumentation Mining
[]
ACL_2017_145
ACL
null
null
true
true
null
[]
ACL_2017_148
ACL
null
null
true
true
Evaluation Metrics for Reading Comprehension: Prerequisite Skills and Readability
[]
ACL_2017_150
ACL
null
null
true
true
Deep Character-Level Neural Machine Translation By Learning Morphology
[]
ACL_2017_169
ACL
null
null
true
true
Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction
[]
ACL_2017_16
ACL
null
null
true
true
Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms
[]
ACL_2017_173
ACL
null
null
true
true
Determining Gains Acquired from Word Embedding Quantitatively using Discrete Distribution Clustering
[]
ACL_2017_178
ACL
null
null
true
true
A Weakly-Supervised Method for Jointly Embedding Concepts, Phrases, and Words
[]
ACL_2017_180
ACL
null
null
true
true
Identifying Products in Online Cybercrime Marketplaces: A Dataset and Fine-grained Domain Adaptation Task
[]
ACL_2017_182
ACL
null
null
true
true
Modeling Contextual Relationships Among Utterances for Multimodal Sentiment Analysis
[]
ACL_2017_18
ACL
null
null
true
true
Attention-over-Attention Neural Networks for Reading Comprehension
[]
ACL_2017_193
ACL
null
null
true
true
null
[]
ACL_2017_19
ACL
null
null
true
true
Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution
[]
ACL_2017_201
ACL
null
null
true
true
Investigating Different Context Types and Representations for Learning Word Embeddings
[]
ACL_2017_214
ACL
null
null
true
true
Exploring Macro Discourse Structure with Macro-micro Unified Primary-secondary Relationship
[]
ACL_2017_216
ACL
null
null
true
true
Topical Coherence in LDA-based Models through Induced Segmentation
[]
ACL_2017_21
ACL
null
null
true
true
Transductive Non-linear Learning for Chinese Hypernym Prediction
[]
ACL_2017_220
ACL
null
null
true
true
null
[]
ACL_2017_222
ACL
null
null
true
true
Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme
[]
ACL_2017_226
ACL
null
null
true
true
null
[]
ACL_2017_237
ACL
null
null
true
true
A New Approach for Measuring Sentiment Orientation based on Multi-Dimensional Vector Space
[]
ACL_2017_239
ACL
null
null
true
true
How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks
[]
ACL_2017_251
ACL
null
null
true
true
null
[]
ACL_2017_256
ACL
null
null
true
true
Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders
[]
ACL_2017_266
ACL
null
null
true
true
Improving sentiment classification with task-specific data
[]
ACL_2017_26
ACL
null
null
true
true
An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge
[]
ACL_2017_270
ACL
null
null
true
true
Enhanced LSTM for Natural Language Inference
[]
ACL_2017_276
ACL
null
null
true
true
Semi-supervised Multitask Learning for Sequence Labeling
[]
ACL_2017_288
ACL
null
null
true
true
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task
[]
ACL_2017_318
ACL
null
null
true
true
Improved Word Representation Learning with Sememes
[]
ACL_2017_31
ACL
null
null
true
true
Event Factuality Identification via Deep Neural Networks
[]
ACL_2017_323
ACL
null
null
true
true
A Neural Local Coherence Model
[]
ACL_2017_326
ACL
null
null
true
true
Adversarial Multi-Criteria Learning for Chinese Word Segmentation
[]
ACL_2017_331
ACL
null
null
true
true
Connecting the dots: Summarizing and Structuring Large Document Collections Using Concept Maps
[]
ACL_2017_333
ACL
null
null
true
true
Selective Encoding for Abstractive Sentence Summarization
[]
ACL_2017_335
ACL
null
null
true
true
Gated Self-Matching Networks for Reading Comprehension and Question Answering
[]
ACL_2017_338
ACL
null
null
true
true
Handling Cold-Start Problem in Review Spam Detection by Jointly Embedding Texts and Behaviors
[]
ACL_2017_33
ACL
null
null
true
true
Linguistically Regularized LSTM for Sentiment Classification
[]
ACL_2017_343
ACL
null
null
true
true
Neural Word Segmentation with Rich Pretraining
[]
ACL_2017_350
ACL
null
null
true
true
null
[]
ACL_2017_352
ACL
null
null
true
true
null
[]
ACL_2017_355
ACL
null
null
true
true
Neural Modeling of Multi-Predicate Interactions for Japanese Predicate Argument Structure Analysis
[]
ACL_2017_365
ACL
null
null
true
true
Learning attention for historical text normalization by learning to pronounce
[]
ACL_2017_367
ACL
null
null
true
true
null
[]
ACL_2017_369
ACL
null
null
true
true
Morphology Generation for Statistical Machine Translation using Deep Learning Techniques
[]
ACL_2017_371
ACL
null
null
true
true
null
[]
ACL_2017_375
ACL
null
null
true
true
CANE: Context-Aware Network Embedding for Relation Modeling
[]
ACL_2017_376
ACL
null
null
true
true
Event-based, Recursive Neural Networks for the Extraction and Aggregation of International Alliance Relations
[]
ACL_2017_37
ACL
null
null
true
true
Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots
[]
ACL_2017_382
ACL
null
null
true
true
Creating Training Corpora for NLG Micro-Planning
[]
ACL_2017_384
ACL
null
null
true
true
Identifying 1950s American Jazz Composers: Fine-Grained IsA Extraction via Modifier Composition
[]
ACL_2017_387
ACL
null
null
true
true
Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network
[]
ACL_2017_388
ACL
null
null
true
true
null
[]
ACL_2017_395
ACL
null
null
true
true
DRL-Sense: Deep Reinforcement Learning for Multi-Sense Word Representations
[]
ACL_2017_419
ACL
null
null
true
true
One-Shot Neural Cross-Lingual Transfer for Paradigm Completion
[]
ACL_2017_433
ACL
null
null
true
true
null
[]
ACL_2017_435
ACL
null
null
true
true
Neural Disambiguation of Causal Lexical Markers based on Context
[]
ACL_2017_440
ACL
null
null
true
true
null
[]
ACL_2017_444
ACL
null
null
true
true
Evaluating Creative Language Generation: The Case of Rap Lyric Ghostwriting
[]
ACL_2017_447
ACL
null
null
true
true
Neural Discourse Structure for Text Categorization
[]
ACL_2017_462
ACL
null
null
true
true
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models
[]
ACL_2017_467
ACL
null
null
true
true
null
[]
ACL_2017_477
ACL
null
null
true
true
From Characters to Words to in Between: Do We Capture Morphology?
[]
ACL_2017_481
ACL
null
null
true
true
null
[]
ACL_2017_483
ACL
null
null
true
true
Here’s My Point: Argumentation Mining with Pointer Networks
[]
ACL_2017_484
ACL
null
null
true
true
null
[]
ACL_2017_489
ACL
null
null
true
true
Combining distributional and referential information for naming objects through cross-modal mapping and direct word prediction
[]
ACL_2017_494
ACL
null
null
true
true
Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules
[]
ACL_2017_496
ACL
null
null
true
true
What do Neural Machine Translation Models Learn about Morphology?
[]
ACL_2017_49
ACL
null
null
true
true
Chunk-based Decoder for Neural Machine Translation
[]
ACL_2017_501
ACL
null
null
true
true
Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task
[]
ACL_2017_503
ACL
null
null
true
true
Probabilistic Regular Graph Languages
[]
ACL_2017_516
ACL
null
null
true
true
Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling
[]
ACL_2017_520
ACL
null
null
true
true
SHAPEWORLD: A new test methodology for multimodal language understanding
[]
ACL_2017_524
ACL
null
null
true
true
A Comparison of Robust Parsing Methods for HPSG
[]
ACL_2017_543
ACL
null
null
true
true
Learning Character-level Compositionality with Visual Features
[]
ACL_2017_553
ACL
null
null
true
true
null
[]
ACL_2017_554
ACL
null
null
true
true
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling
[]
ACL_2017_557
ACL
null
null
true
true
End-to-End Neural Relation Extraction with Global Optimization
[]
ACL_2017_561
ACL
null
null
true
true
Semi-supervised sequence tagging with bidirectional language models
[]
ACL_2017_562
ACL
null
null
true
true
Zero-Shot Relation Extraction via Reading Comprehension
[]
ACL_2017_563
ACL
null
null
true
true
Exploring Vector Spaces for Semantic Relations
[]
ACL_2017_564
ACL
null
null
true
true
Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
[]
ACL_2017_56
ACL
null
null
true
true
Ngram2vec: Learning Improved Word Representations from Ngram Co-occurrence Statistics
[]
ACL_2017_578
ACL
null
null
true
true
Robust Incremental Neural Semantic Graph Parsing
[]
ACL_2017_579
ACL
null
null
true
true
MinIE: Minimizing Facts in Open Information Extraction
[]
ACL_2017_588
ACL
null
null
true
true
Rare Entity Prediction: Language Understanding with External Knowledge using Hierarchical LSTMs
[ "Peter Ackroyd" ]
ACL_2017_606
ACL
null
null
true
true
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
[]
ACL_2017_614
ACL
null
null
true
true
null
[]
ACL_2017_619
ACL
null
null
true
true
A Corpus of Annotated Revisions for Studying Argumentative Writing
[]
ACL_2017_627
ACL
null
null
true
true
Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access
[]
End of preview.

Raw Review Dataset for Reviewer2

This is the raw version of our dataset. The cleaned data files that can be directly used for fine-tuning is in this directory.

Dataset Structure

The folders are structured in the following way:

venue
|--venue_year
   |--venue_year_metadata
      |--venue_year_id1_metadata.json
      |--venue_year_id2_metadata.json
      ...
   |--venue_year_paper
      |--venue_year_id1_paper.json
      |--venue_year_id2_paper.json
      ...
   |--venue_year_review
      |--venue_year_id1_review.json
      |--venue_year_id2_review.json
      ...
   |--venue_year_pdf
      |--venue_year_id1_pdf.pdf
      |--venue_year_id2_pdf.pdf
      ...

Dataset Content

Paper Contents

  • title: title of the paper
  • authors: list of author names
  • emails: list of author emails
  • sections: list of sections of the paper
    • heading: heading of the section
    • text: text of the section
  • references: list of references of the paper
    • title: title of the reference
    • author: list of author names of the reference
    • venue: venue of the reference
    • citeRegEx: citation expression
    • shortCiteRegEx: short citation expression
    • year: publication year of the reference
  • referenceMentions: the location of the reference in the paper
    • referenceID: numerical reference id
    • context: context of the reference in the paper
    • startOffset: start index of the context
    • endOffset: end index of the context
  • year: year of publication
  • abstractText: abstract of the paper

Metadata Contents

  • id: unique id of the paper
  • conference: venue for the paper
  • decision: final decision for the paper (accept/reject)
  • url: link to the PDF of the paper
  • review_url: link to the review of the paper
  • title: title of the paper
  • authors: list of the authors of the paper

Dataset Sources

We incorporate parts of the PeerRead and NLPeer datasets along with an update-to-date crawl from ICLR and NeurIPS on OpenReview and NeurIPS Proceedings.

Citation

If you find this dataset useful in your research, please cite the following paper:

@misc{gao2024reviewer2,
      title={Reviewer2: Optimizing Review Generation Through Prompt Generation}, 
      author={Zhaolin Gao and Kianté Brantley and Thorsten Joachims},
      year={2024},
      eprint={2402.10886},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
Downloads last month
36