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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 Hits 1 – 20 of 29 1 A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples ... 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; Che, Wanxiang; Cohen, Shay B.. - : Underline Science Inc., 2021 BASE Show details 2 A Root of a Problem: Optimizing Single-Root Dependency Parsing ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cohen, Shay B.; Stanojević, Miloš. - : Underline Science Inc., 2021 BASE Show details 3 Unlexicalized Transition-based Discontinuous Constituency Parsing Coavoux, Maximin; Crabbé, Benoît; Cohen, Shay B. In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02150073 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2019, 7, pp.73--89. ⟨10.1162/tacl_a_00255⟩ (2019) Abstract: Lexicalized parsing models are based on the assumptions that (i) constituents are organized around a lexical head and (ii) bilexical statistics are crucial to solve ambiguities. In this paper, we introduce an unlexicalized transition-based parser for discontinuous constituency structures, based on a structure-label transition system and a bi-LSTM scoring system. We compare it with lexicalized parsing models in order to address the question of lexicalization in the context of discontinuous constituency parsing. Our experiments show that unlexicalized models systematically achieve higher results than lexicalized models, and provide additional empirical evidence that lexicalization is not necessary to achieve strong parsing results. Our best unlexicalized model sets a new state of the art on English and German discontinuous constituency treebanks. We further provide a per-phenomenon analysis of its errors on discontinuous constituents. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] URL: https://doi.org/10.1162/tacl_a_00255 https://hal.archives-ouvertes.fr/hal-02150073 BASE Hide details 4 Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic Oracle Coavoux, Maximin; Cohen, Shay B. In: 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT 2019) ; https://hal.archives-ouvertes.fr/hal-02150076 ; 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT 2019), Jun 2019, Minneapolis, MN, United States. pp.204--217 ; https://naacl2019.org/ (2019) BASE Show details 5 Unlexicalized Transition-based Discontinuous Constituency Parsing ... Coavoux, Maximin; Crabbé, Benoît; Cohen, Shay B.. - : arXiv, 2019 BASE Show details 6 Unlexicalized Transition-based Discontinuous Constituency Parsing Coavoux, Maximin; Crabbé, Benoît; Cohen, Shay B. In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 73-89 (2019) (2019) BASE Show details 7 Privacy-preserving Neural Representations of Text Coavoux, Maximin; Narayan, Shashi; Cohen, Shay B. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing ; 2018 Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-02135081 ; 2018 Conference on Empirical Methods in Natural Language Processing, Nov 2018, Brussels, Belgium. pp.1--10 (2018) BASE Show details 8 Empirical Risk Minimization for Probabilistic Grammars: Sample Complexity and Hardness of Learning ... Cohen, Shay B.; Smith, Noah A.. - : Figshare, 2018 BASE Show details 9 Unsupervised Bilingual POS Tagging with Markov Random Fields ... Desai Chen; Dyer, Chris; Cohen, Shay B.. - : Figshare, 2018 BASE Show details 10 Unsupervised Bilingual POS Tagging with Markov Random Fields ... Desai Chen; Dyer, Chris; Cohen, Shay B.. - : Figshare, 2018 BASE Show details 11 Multilingual Clustering of Streaming News ... Miranda, Sebastião; Znotiņš, Artūrs; Cohen, Shay B.. - : arXiv, 2018 BASE Show details 12 The Summa Platform Prototype ... Liepins, Renars; Germann, Ulrich; Barzdins, Guntis. - : Zenodo, 2017 BASE Show details 13 The Summa Platform Prototype ... Liepins, Renars; Germann, Ulrich; Barzdins, Guntis. - : Zenodo, 2017 BASE Show details 14 Whodunnit? Crime Drama as a Case for Natural Language Understanding ... Frermann, Lea; Cohen, Shay B.; Lapata, Mirella. - : arXiv, 2017 BASE Show details 15 Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing ... Narayan, Shashi; Reddy, Siva; Cohen, Shay B.. - : arXiv, 2016 BASE Show details 16 Paraphrase Generation From Latent-Variable Pcfgs For Semantic Parsing ... Narayan, Shashi; Reddy, Siva; Cohen, Shay B.. - : Zenodo, 2016 BASE Show details 17 Paraphrase Generation From Latent-Variable Pcfgs For Semantic Parsing ... Narayan, Shashi; Reddy, Siva; Cohen, Shay B.. - : Zenodo, 2016 BASE Show details 18 Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing ... Narayan, Shashi; Reddy, Siva; Cohen, Shay B.. - : Zenodo, 2016 BASE Show details 19 Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing ... Narayan, Shashi; Reddy, Siva; Cohen, Shay B.. - : Zenodo, 2016 BASE Show details 20 Encoding Prior Knowledge with Eigenword Embeddings ... Osborne, Dominique; Narayan, Shashi; Cohen, Shay B.. - : arXiv, 2015 BASE Show details Page: 1 2

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