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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; Ren, Hongyu; Liang, Percy; Manning, Christopher D.; Leskovec, Jure. - : arXiv, 2022 Abstract: Answering complex questions about textual narratives requires reasoning over both stated context and the world knowledge that underlies it. However, pretrained language models (LM), the foundation of most modern QA systems, do not robustly represent latent relationships between concepts, which is necessary for reasoning. While knowledge graphs (KG) are often used to augment LMs with structured representations of world knowledge, it remains an open question how to effectively fuse and reason over the KG representations and the language context, which provides situational constraints and nuances. In this work, we propose GreaseLM, a new model that fuses encoded representations from pretrained LMs and graph neural networks over multiple layers of modality interaction operations. Information from both modalities propagates to the other, allowing language context representations to be grounded by structured world knowledge, and allowing linguistic nuances (e.g., negation, hedging) in the context to inform the ... : Published at ICLR 2022. All code, data, and pretrained models are available at https://github.com/snap-stanford/GreaseLM ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://arxiv.org/abs/2201.08860 https://dx.doi.org/10.48550/arxiv.2201.08860 BASE Hide 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 BASE Show 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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