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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...11 Hits 1 – 20 of 220 1 Multitask Pointer Network for Multi-Representational Parsing Fernández-González, Daniel; Gómez-Rodríguez, Carlos. - : Elsevier, 2022 BASE Show details 2 Joint learning of morphology and syntax with cross-level contextual information flow Can Buglalilar, Burcu; Aleçakır, Hüseyin; Manandhar, Suresh... In: 2022 ; 1 ; 33 (2022) BASE Show details 3 Analyse en dépendances du français avec des plongements contextualisés Grobol, Loïc; Crabbé, Benoît In: 28e Conférence sur le Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-03223424 ; 28e Conférence sur le Traitement Automatique des Langues Naturelles, Jun 2021, Lille (virtuel), France (2021) BASE Show details 4 To be or not to be adultlike in syntax: An experimental study of language acquisition and processing in children ... Lassotta, Romy. - : Université de Genève, 2021 BASE Show details 5 IWPT 2021 Shared Task Data and System Outputs Zeman, Daniel; Bouma, Gosse; Seddah, Djamé. - : Universal Dependencies Consortium, 2021 BASE Show details 6 Training corpus ssj500k 2.3 Krek, Simon; Dobrovoljc, Kaja; Erjavec, Tomaž. - : Centre for Language Resources and Technologies, University of Ljubljana, 2021 BASE Show details 7 PLPrepare: A Grammar Checker for Challenging Cases Hoyos, Jacob In: Electronic Theses and Dissertations (2021) BASE Show details 8 To be or not to be adultlike in syntax: An experimental study of language acquisition and processing in children Lassotta, Romy. - : Université de Genève, 2021 BASE Show details 9 Resourceful at Any Size: A Predictive Methodology Using Linguistic Corpus Metrics for Multi-Source Training in Neural Dependency Parsing Gokcen, Ajda. - 2021 Abstract: Thesis (Ph.D.)--University of Washington, 2021 ; Multilingual modeling comes up in natural language processing at any scale. High-resource language corpora train high-performing models, and can be combined with other language corpora of all sizes to make better models for low-resource languages. Projects like Universal Dependencies even make it possible to train highly multilingual models from standardized morphosyntactic labels. Multilingual (or, more generally, multi-source) training does not consistently improve modeling performance, however. With an abundance of language resources comes a difficult design choice: which corpora will train better together rather than separately? More specifically, when is it worthwhile to supplement (i.e., concatenate) one corpus with another during training, rather than training on the first corpus alone? Approaches to selecting and evaluating candidate combinations tend toward two extremes: ad hoc or exhaustive. In this work, I put forth an alternative, predictive methodology for outcomes of concatenative training in dependency parsing. I leverage treebanks from the Universal Dependencies framework to assess the utility of linguistic corpus metrics in multi-source modeling. This approach is both robust and practical, using computationally simple metrics that expand upon intuitions of linguistic similarity, and making it possible to reasonably predict which conditions will yield significant improvement for a target corpus. Although the results are specific to a particular family of models and the task of dependency parsing, the approach holds promise for any number of natural language processing applications. Keyword: Computational Linguistics; Computer science; Corpus Linguistics; Dependency Parsing; Linguistics; Multilingual Modeling; Multitask Modeling; Natural Language Processing URL: http://hdl.handle.net/1773/48283 BASE Hide details 10 Treebank embedding vectors for out-of-domain dependency parsing Wagner, Joachim; Barry, James; Foster, Jennifer In: Wagner, Joachim orcid:0000-0002-8290-3849 , Barry, James orcid:0000-0003-3051-585X and Foster, Jennifer orcid:0000-0002-7789-4853 (2020) Treebank embedding vectors for out-of-domain dependency parsing. In: 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), 05-10 Jul 2020, Online (virtual conference). (2020) BASE Show details 11 Bootstrap methods for multi-task dependency parsing in low-resource conditions ; Méthodes d’amorçage pour l’analyse en dépendances de langues peu dotées Lim, Kyungtae. - : HAL CCSD, 2020 In: https://tel.archives-ouvertes.fr/tel-03477961 ; Linguistics. Université Paris sciences et lettres, 2020. English. ⟨NNT : 2020UPSLE027⟩ (2020) BASE Show details 12 Extrinsic Evaluation of French Dependency Parsers on a Specialized Corpus: Comparison of Distributional Thesauri Tanguy, Ludovic; Brunet, Pauline; Ferret, Olivier In: 12th Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-02611042 ; 12th Language Resources and Evaluation Conference, May 2020, Marseille, France. pp.5822-5830 (2020) BASE Show details 13 IWPT 2020 Shared Task Data and System Outputs Zeman, Daniel; Bouma, Gosse; Seddah, Djamé. - : Universal Dependencies Consortium, 2020 BASE Show details 14 On understanding character-level models for representing morphology ... Vania, Clara. - : The University of Edinburgh, 2020 BASE Show details 15 Linguatec Tolosa Treebank ... Miletic, Aleksandra; Bras, Myriam; Esher, Louise. - : Zenodo, 2020 BASE Show details 16 Linguatec Tolosa Treebank ... Miletic, Aleksandra; Bras, Myriam; Esher, Louise. - : Zenodo, 2020 BASE Show details 17 Demographic-Aware Natural Language Processing Garimella, Aparna. - 2020 BASE Show details 18 On understanding character-level models for representing morphology Vania, Clara. - : The University of Edinburgh, 2020 BASE Show details 19 Self attended stack pointer networks for learning long term dependencies Can, Burcu; Tuç, Salih. - : Association for Computational Linguistics, 2020 BASE Show details 20 Annotation syntaxique automatique de la partie orale du ORFÉO Nasr, Alexis; Dary, Franck; Béchet, Frédéric... In: Langages, N 219, 3, 2020-08-11, pp.87-102 (2020) BASE Show details Page: 1 2 3 4 5...11

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