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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 Hits 1 – 9 of 9 1 Unsupervised Learning for Handling Code-Mixed Data: A Case Study on POS Tagging of North-African Arabizi Dialect Srivastava, Abhishek; Muller, Benjamin; Seddah, Djamé In: EurNLP - First annual EurNLP ; https://hal.archives-ouvertes.fr/hal-02270527 ; EurNLP - First annual EurNLP, Oct 2019, Londres, United Kingdom (2019) BASE Show details 2 CamemBERT: a Tasty French Language Model Martin, Louis; Muller, Benjamin; Ortiz Suárez, Pedro Javier... In: https://hal.inria.fr/hal-02445946 ; 2019 (2019) BASE Show details 3 Enhancing BERT for Lexical Normalization Muller, Benjamin; Sagot, Benoît; Seddah, Djamé In: The 5th Workshop on Noisy User-generated Text (W-NUT) ; https://hal.inria.fr/hal-02294316 ; The 5th Workshop on Noisy User-generated Text (W-NUT), Nov 2019, Hong Kong, China (2019) BASE Show details 4 What does BERT learn about the structure of language? Jawahar, Ganesh; Sagot, Benoît; Seddah, Djamé In: ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02131630 ; ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Jul 2019, Florence, Italy (2019) Abstract: International audience ; BERT is a recent language representation model that has surprisingly performed well in diverse language understanding benchmarks. This result indicates the possibility that BERT networks capture structural information about language. In this work, we provide novel support for this claim by performing a series of experiments to unpack the elements of English language structure learned by BERT. We first show that BERT's phrasal representation captures phrase-level information in the lower layers. We also show that BERT's intermediate layers encode a rich hierarchy of linguistic information, with surface features at the bottom, syntactic features in the middle and semantic features at the top. BERT turns out to require deeper layers when long-distance dependency information is required, e.g.~to track subject-verb agreement. Finally, we show that BERT representations capture linguistic information in a compositional way that mimics classical, tree-like structures. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] URL: https://hal.inria.fr/hal-02131630 https://hal.inria.fr/hal-02131630/file/intbert_acl19paper-3.pdf https://hal.inria.fr/hal-02131630/document BASE Hide details 5 Contextualized Diachronic Word Representations Jawahar, Ganesh; Seddah, Djamé In: 1st International Workshop on Computational Approaches to Historical Language Change 2019 (colocated with ACL 2019) ; https://hal.archives-ouvertes.fr/hal-02194763 ; 1st International Workshop on Computational Approaches to Historical Language Change 2019 (colocated with ACL 2019), Aug 2019, Florence, Italy (2019) BASE Show details 6 A Comparison between NMT and PBSMT Performance for Translating Noisy User-Generated Content Rosales Nunez, José Carlos; Seddah, Djamé; Wisniewski, Guillaume In: The 22nd Nordic Conference on Computational Linguistics (NoDaLiDa’19) ; https://hal.archives-ouvertes.fr/hal-02270524 ; The 22nd Nordic Conference on Computational Linguistics (NoDaLiDa’19), Sep 2019, Turku, Finland ; https://nodalida2019.org/index.html (2019) BASE Show details 7 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details 8 Universal Dependencies 2.4 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019 BASE Show details 9 Linked Open Treebanks. Interlinking Syntactically Annotated Corpora in the LiLa Knowledge Base of Linguistic Resources for Latin Mambrini, Francesco (orcid:0000-0003-0834-7562); Passarotti, Marco (orcid:0000-0002-9806-7187). - : Association for Computational Linguistics, 2019. : country:FRA, 2019. : place:Paris, 2019 BASE Show details

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