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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 Hits 1 – 20 of 113 1 GreaseLM: Graph REASoning Enhanced Language Models for Question Answering ... Zhang, Xikun; Bosselut, Antoine; Yasunaga, Michihiro. - : arXiv, 2022 BASE Show details 2 Universal Dependencies 2.9 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 3 Universal Dependencies 2.8.1 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 4 Universal Dependencies 2.8 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 5 Human-like informative conversations: Better acknowledgements using conditional mutual information ... Paranjape, Ashwin; Manning, Christopher D.. - : arXiv, 2021 BASE Show details 6 Universal Dependencies ... NAACL 2021 2021; de Marneffe, Marie-Catherine; Manning, Christopher. - : Underline Science Inc., 2021 BASE Show details 7 ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts ... Koreeda, Yuta; Manning, Christopher D.. - : arXiv, 2021 Abstract: Reviewing contracts is a time-consuming procedure that incurs large expenses to companies and social inequality to those who cannot afford it. In this work, we propose "document-level natural language inference (NLI) for contracts", a novel, real-world application of NLI that addresses such problems. In this task, a system is given a set of hypotheses (such as "Some obligations of Agreement may survive termination.") and a contract, and it is asked to classify whether each hypothesis is "entailed by", "contradicting to" or "not mentioned by" (neutral to) the contract as well as identifying "evidence" for the decision as spans in the contract. We annotated and release the largest corpus to date consisting of 607 annotated contracts. We then show that existing models fail badly on our task and introduce a strong baseline, which (1) models evidence identification as multi-label classification over spans instead of trying to predict start and end tokens, and (2) employs more sophisticated context segmentation ... : Accepted at the Findings of the Association for Computational Linguistics: EMNLP 2021 ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.2110.01799 https://arxiv.org/abs/2110.01799 BASE Hide details 8 ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; D. Manning, Christopher; Koreeda, Yuta. - : Underline Science Inc., 2021 BASE Show details 9 Conditional probing: measuring usable information beyond a baseline ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ethayarajh, Kawin; Hewitt, John. - : Underline Science Inc., 2021 BASE Show details 10 Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Fei-Fei, Li; Karamcheti, Siddharth. - : Underline Science Inc., 2021 BASE Show details 11 Human-like informative conversations: Better acknowledgements using conditional mutual information ... NAACL 2021 2021; Manning, Christopher; Paranjape, Ashwin. - : Underline Science Inc., 2021 BASE Show details 12 Biomedical and clinical English model packages for the Stanza Python NLP library Zhang, Yuhao; Zhang, Yuhui; Qi, Peng... In: J Am Med Inform Assoc (2021) BASE Show details 13 Universal Dependencies 2.7 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 14 Universal Dependencies 2.6 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 15 Stanza: A Python Natural Language Processing Toolkit for Many Human Languages ... Qi, Peng; Zhang, Yuhao; Zhang, Yuhui. - : arXiv, 2020 BASE Show details 16 Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection ... Nivre, Joakim; de Marneffe, Marie-Catherine; Ginter, Filip. - : arXiv, 2020 BASE Show details 17 Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation ... Dhole, Kaustubh D.; Manning, Christopher D.. - : arXiv, 2020 BASE Show details 18 Finding Universal Grammatical Relations in Multilingual BERT ... Chi, Ethan A.; Hewitt, John; Manning, Christopher D.. - : arXiv, 2020 BASE Show details 19 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details 20 Universal Dependencies 2.4 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019 BASE Show details Page: 1 2 3 4 5 6

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