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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 Hits 1 – 20 of 94 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 Syntactic Nuclei in Dependency Parsing -- A Multilingual Exploration ... Basirat, Ali; Nivre, Joakim. - : arXiv, 2021 BASE Show details 7 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 8 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 9 Attention Can Reflect Syntactic Structure (If You Let It) ... Ravishankar, Vinit; Kulmizev, Artur; Abdou, Mostafa. - : arXiv, 2021 BASE Show details 10 What Should/Do/Can LSTMs Learn When Parsing Auxiliary Verb Constructions? ... NAACL 2021 2021; de Lhoneux, Miryam; Nivre, Joakim; Stymne, Sara. - : Underline Science Inc., 2021 Abstract: Read the paper on the folowing link: https://direct.mit.edu/coli/article/46/4/763/97325/What-Should-Do-Can-LSTMs-Learn-When-Parsing Abstract: There is a growing interest in investigating what neural NLP models learn about language. A prominent open question is the question of whether or not it is necessary to model hierarchical structure. We present a linguistic investigation of a neural parser adding insights to this question. We look at transitivity and agreement information of auxiliary verb constructions (AVCs) in comparison to finite main verbs (FMVs). This comparison is motivated by theoretical work in dependency grammar and in particular the work of Tesnière (1959) where AVCs and FMVs are both instances of a nucleus, the basic unit of syntax. An AVC is a dissociated nucleus, it consists of at least two words, and an FMV is its non-dissociated counterpart, consisting of exactly one word. We suggest that the representation of AVCs and FMVs should capture similar information. We use diagnostic ... Keyword: Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing URL: https://underline.io/lecture/20052-what-shoulddashdodashcan-lstms-learn-when-parsing-auxiliary-verb-constructionsquestion https://dx.doi.org/10.48448/ys11-hq56 BASE Hide details 11 Schrödinger's Tree -- On Syntax and Neural Language Models ... Kulmizev, Artur; Nivre, Joakim. - : arXiv, 2021 BASE Show details 12 Universal Dependencies 2.7 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 13 Universal Dependencies 2.6 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 14 Køpsala: Transition-Based Graph Parsing via Efficient Training and Effective Encoding ... Hershcovich, Daniel; de Lhoneux, Miryam; Kulmizev, Artur. - : arXiv, 2020 BASE Show details 15 Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : arXiv, 2020 BASE Show details 16 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 17 Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection ... Nivre, Joakim; de Marneffe, Marie-Catherine; Ginter, Filip. - : arXiv, 2020 BASE Show details 18 Do Neural Language Models Show Preferences for Syntactic Formalisms? ... Kulmizev, Artur; Ravishankar, Vinit; Abdou, Mostafa. - : arXiv, 2020 BASE Show details 19 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 20 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details Page: 1 2 3 4 5

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