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FlauBERT : des modèles de langue contextualisés pré-entraînés pour le français (FlauBERT : Unsupervised Language Model Pre-training for French).

, , , , , , , , , and . JEP-TALN-RECITAL (2), page 268-278. ATALA et AFCP, (2020)

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Opening the Vocabulary of Neural Language Models with Character-level Word Represen- Tations, and . (2016)LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech., , , , , , , , , and 12 other author(s). CoRR, (2023)Leveraging the structure of dynamical systems for data-driven modeling., , , , and . CoRR, (2021)LIMSI's Statistical Translation Systems for WMT'09., , , and . WMT@EACL, page 100-104. Association for Computational Linguistics, (2009)Perception of the evolution of prosody in the French broadcast news style., , and . INTERSPEECH, page 2531-2534. ISCA, (2009)LIMSI @ IWSLT 2010., , , , , and . IWSLT, page 105-112. ISCA, (2010)Designing an Improved Discriminative Word Aligner., , , and . Int. J. Comput. Linguistics Appl., 2 (1-2): 239-255 (2011)Adapting without forgetting: KnowBert-UMLS., , , , , and . WiMob, page 19-24. IEEE, (2022)Apprentissage de plongements de mots dynamiques avec régularisation de la dérive (Learning dynamic word embeddings with drift regularisation)., and . PFIA (Articles longs), page 13-26. ATALA, (2019)Oublier ce qu'on sait, pour mieux apprendre ce qu'on ne sait pas : une étude sur les contraintes de type dans les modèles CRF., , , , and . TALN (long papers), page 37-48. ATALA, (2015)