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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 Hits 1 – 20 of 72 1 Universals of Linguistic Idiosyncrasy in Multilingual Computational Linguistics (Dagstuhl Seminar 21351) Croft, William; Savary, Agata; Baldwin, Timothy. - : Dagstuhl Reports. DagRep, Volume 11, Issue 7, 2021 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 Universal Dependencies ... NAACL 2021 2021; de Marneffe, Marie-Catherine; Manning, Christopher. - : Underline Science Inc., 2021 BASE Show details 6 Revisiting Negation in Neural Machine Translation ... 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; Nivre, Joakim; Rönchen, Philipp. - : Underline Science Inc., 2021 BASE Show details 7 Universals of Linguistic Idiosyncrasy in Multilingual Computational Linguistics (Dagstuhl Seminar 21351) ... Baldwin, Timothy; Croft, William; Nivre, Joakim. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021 BASE Show details 8 Attention Can Reflect Syntactic Structure (If You Let It) ... Ravishankar, Vinit; Kulmizev, Artur; Abdou, Mostafa. - : arXiv, 2021 BASE Show details 9 What Should/Do/Can LSTMs Learn When Parsing Auxiliary Verb Constructions? ... NAACL 2021 2021; de Lhoneux, Miryam; Nivre, Joakim. - : Underline Science Inc., 2021 BASE Show details 10 Universal Dependencies 2.7 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 11 Universal Dependencies 2.6 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 12 Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : International Committee on Computational Linguistics, 2020 BASE Show details 13 Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English Tang, Gongbo; Sennrich, Rico; Nivre, Joakim In: Tang, Gongbo; Sennrich, Rico; Nivre, Joakim (2020). Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English. In: Proceedings of the 28th International Conference on Computational Linguistics, Barcelona, Spain, 8 December 2020 - 13 December 2020, 4251-4262. (2020) BASE Show details 14 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details 15 Universal Dependencies 2.4 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019 BASE Show details 16 Encoders Help You Disambiguate Word Senses in Neural Machine Translation ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : Association for Computational Linguistics, 2019 BASE Show details 17 Encoders Help You Disambiguate Word Senses in Neural Machine Translation ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : arXiv, 2019 Abstract: Neural machine translation (NMT) has achieved new state-of-the-art performance in translating ambiguous words. However, it is still unclear which component dominates the process of disambiguation. In this paper, we explore the ability of NMT encoders and decoders to disambiguate word senses by evaluating hidden states and investigating the distributions of self-attention. We train a classifier to predict whether a translation is correct given the representation of an ambiguous noun. We find that encoder hidden states outperform word embeddings significantly which indicates that encoders adequately encode relevant information for disambiguation into hidden states. Decoders could provide further relevant information for disambiguation. Moreover, the attention weights and attention entropy show that self-attention can detect ambiguous nouns and distribute more attention to the context. Note that this is a revised version. The content related to decoder hidden states has been updated. ... : Update with corrections. Here is the link to the erratum: https://www.aclweb.org/anthology/D19-1149e1.pdf ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1908.11771 https://arxiv.org/abs/1908.11771 BASE Hide details 18 Universal Dependencies 2.3 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 19 Universal Dependencies 2.2 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 20 CoNLL 2018 Shared Task System Outputs Zeman, Daniel; Potthast, Martin; Duthoo, Elie. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2018 BASE Show details Page: 1 2 3 4

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