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"description": "SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after\nGLUE with a new set of more difficult language understanding tasks, improved\nresources, and a new public leaderboard.\n\nBoolQ (Boolean Questions, Clark et al., 2019a) is a QA task where each example consists of a short\npassage and a yes/no question about the passage. The questions are provided anonymously and\nunsolicited by users of the Google search engine, and afterwards paired with a paragraph from a\nWikipedia article containing the answer. Following the original work, we evaluate with accuracy.", |
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"citation": "@inproceedings{clark2019boolq,\n title={BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions},\n author={Clark, Christopher and Lee, Kenton and Chang, Ming-Wei, and Kwiatkowski, Tom and Collins, Michael, and Toutanova, Kristina},\n booktitle={NAACL},\n year={2019}\n}\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},\n journal={arXiv preprint arXiv:1905.00537},\n year={2019}\n}\n\nNote that each SuperGLUE dataset has its own citation. Please see the source to\nget the correct citation for each contained dataset.\n", |
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"citation": "@inproceedings{roemmele2011choice,\n title={Choice of plausible alternatives: An evaluation of commonsense causal reasoning},\n author={Roemmele, Melissa and Bejan, Cosmin Adrian and Gordon, Andrew S},\n booktitle={2011 AAAI Spring Symposium Series},\n year={2011}\n}\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},\n journal={arXiv preprint arXiv:1905.00537},\n year={2019}\n}\n\nNote that each SuperGLUE dataset has its own citation. Please see the source to\nget the correct citation for each contained dataset.\n", |
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"description": "SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after\nGLUE with a new set of more difficult language understanding tasks, improved\nresources, and a new public leaderboard.\n\nThe Multi-Sentence Reading Comprehension dataset (MultiRC, Khashabi et al., 2018)\nis a true/false question-answering task. Each example consists of a context paragraph, a question\nabout that paragraph, and a list of possible answers to that question which must be labeled as true or\nfalse. Question-answering (QA) is a popular problem with many datasets. We use MultiRC because\nof a number of desirable properties: (i) each question can have multiple possible correct answers,\nso each question-answer pair must be evaluated independent of other pairs, (ii) the questions are\ndesigned such that answering each question requires drawing facts from multiple context sentences,\nand (iii) the question-answer pair format more closely matches the API of other SuperGLUE tasks\nthan span-based extractive QA does. The paragraphs are drawn from seven domains including news,\nfiction, and historical text.", |
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"citation": "@inproceedings{MultiRC2018,\n author = {Daniel Khashabi and Snigdha Chaturvedi and Michael Roth and Shyam Upadhyay and Dan Roth},\n title = {Looking Beyond the Surface:A Challenge Set for Reading Comprehension over Multiple Sentences},\n booktitle = {Proceedings of North American Chapter of the Association for Computational Linguistics (NAACL)},\n year = {2018}\n}\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},\n journal={arXiv preprint arXiv:1905.00537},\n year={2019}\n}\n\nNote that each SuperGLUE dataset has its own citation. Please see the source to\nget the correct citation for each contained dataset.\n", |
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"description": "SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after\nGLUE with a new set of more difficult language understanding tasks, improved\nresources, and a new public leaderboard.\n\n(Reading Comprehension with Commonsense Reasoning Dataset, Zhang et al., 2018) is a\nmultiple-choice QA task. Each example consists of a news article and a Cloze-style question about\nthe article in which one entity is masked out. The system must predict the masked out entity from a\ngiven list of possible entities in the provided passage, where the same entity may be expressed using\nmultiple different surface forms, all of which are considered correct. Articles are drawn from CNN\nand Daily Mail. Following the original work, we evaluate with max (over all mentions) token-level\nF1 and exact match (EM).", |
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"citation": "@article{zhang2018record,\n title={Record: Bridging the gap between human and machine commonsense reading comprehension},\n author={Zhang, Sheng and Liu, Xiaodong and Liu, Jingjing and Gao, Jianfeng and Duh, Kevin and Van Durme, Benjamin},\n journal={arXiv preprint arXiv:1810.12885},\n year={2018}\n}\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},\n journal={arXiv preprint arXiv:1905.00537},\n year={2019}\n}\n\nNote that each SuperGLUE dataset has its own citation. Please see the source to\nget the correct citation for each contained dataset.\n", |
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"description": "SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after\nGLUE with a new set of more difficult language understanding tasks, improved\nresources, and a new public leaderboard.\n\nWinogender is designed to measure gender\nbias in coreference resolution systems. We use the Diverse Natural Language Inference Collection\n(DNC; Poliak et al., 2018) version that casts Winogender as a textual entailment task. Each example\nconsists of a premise sentence with a male or female pronoun and a hypothesis giving a possible\nantecedent of the pronoun. Examples occur in minimal pairs, where the only difference between\nan example and its pair is the gender of the pronoun in the premise. Performance on Winogender\nis measured with both accuracy and the gender parity score: the percentage of minimal pairs for\nwhich the predictions are the same. We note that a system can trivially obtain a perfect gender parity\nscore by guessing the same class for all examples, so a high gender parity score is meaningless unless\naccompanied by high accuracy. As a diagnostic test of gender bias, we view the schemas as having high\npositive predictive value and low negative predictive value; that is, they may demonstrate the presence\nof gender bias in a system, but not prove its absence.\n", |
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"citation": "@inproceedings{rudinger-EtAl:2018:N18,\n author = {Rudinger, Rachel and Naradowsky, Jason and Leonard, Brian and {Van Durme}, Benjamin},\n title = {Gender Bias in Coreference Resolution},\n booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},\n month = {June},\n year = {2018},\n address = {New Orleans, Louisiana},\n publisher = {Association for Computational Linguistics}\n}\n\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},\n journal={arXiv preprint arXiv:1905.00537},\n year={2019}\n}\n\nNote that each SuperGLUE dataset has its own citation. Please see the source to\nget the correct citation for each contained dataset.\n", |
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"homepage": "https://github.com/rudinger/winogender-schemas", |
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"license": "", |
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