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Question Answering with Hybrid Data and Models ; Question-réponse utilisant des données et modèles hybrides
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In: https://tel.archives-ouvertes.fr/tel-02890467 ; Document and Text Processing. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASS024⟩ (2020)
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A Metric Learning Approach to Misogyny Categorization
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In: Proceedings of the 5th Workshop on Representation Learning for NLP ; Workshop on Representation Learning for NLP ; https://hal.archives-ouvertes.fr/hal-02989293 ; Workshop on Representation Learning for NLP, Jul 2020, Online, France. pp.89-94, ⟨10.18653/v1/2020.repl4nlp-1.12⟩ (2020)
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Neural Networks approaches focused on French Spoken Language Understanding: application to the MEDIA Evaluation Task
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In: In Proceedings of The 28th International Conference on Computational Linguistics (COLING’2020), 2020 ; https://hal.archives-ouvertes.fr/hal-03007482 ; In Proceedings of The 28th International Conference on Computational Linguistics (COLING’2020), 2020, Dec 2020, Barcelona (online), Spain (2020)
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Abstract:
International audience ; In this paper, we present a study on a French Spoken Language Understanding (SLU) task: the MEDIA task. Many works and studies have been proposed for many tasks, but most of them are focused on English language and tasks. The exploration of a richer language like French within the framework of a SLU task implies to recent approaches to handle this difficulty. Since the MEDIA task seems to be one of the most difficult, according to several previous studies, we propose to explore Neural Networks approaches focusing of three aspects: firstly, the Neu-ral Network inputs and more specifically the word embeddings; secondly, we compared French version of BERT against the best setup through different ways; Finally, the comparison against State-of-the-Art approaches. Results show that the word embeddings trained on a small corpus need to be updated during SLU model training. Furthermore, the French BERT fine-tuned approaches outperform the classical Neural Network Architectures and achieves state of the art results. However, the contextual embeddings extracted from one of the French BERT approaches achieve comparable results in comparison to word embedding, when integrated into the proposed neural architecture.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
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URL: https://hal.archives-ouvertes.fr/hal-03007482/file/Coling2020%283%29.pdf
https://hal.archives-ouvertes.fr/hal-03007482
https://hal.archives-ouvertes.fr/hal-03007482/document
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Span-based discontinuous constituency parsing: a family of exact chart-based algorithms with time complexities from O(n^6) down to O(n^3)
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) ; Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-03029253 ; Empirical Methods in Natural Language Processing, Nov 2020, Punta Cana (virtual), Dominican Republic (2020)
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Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic Programming
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In: 57th annual meeting of Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03029255 ; 57th annual meeting of Association for Computational Linguistics, Jul 2019, Florence, Italy (2019)
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Going beyond the sentence : Contextual Machine Translation of Dialogue ; Au-delà de la phrase : traduction automatique de dialogue en contexte
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In: https://tel.archives-ouvertes.fr/tel-02004683 ; Computation and Language [cs.CL]. Université Paris Saclay (COmUE), 2018. English. ⟨NNT : 2018SACLS524⟩ (2018)
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SYSTRAN Participation to the WMT2018 Shared Task on Parallel Corpus Filtering
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In: Proceedings of the Third Conference on Machine Translation: Shared Task Papers ; https://hal.archives-ouvertes.fr/hal-02315344 ; Proceedings of the Third Conference on Machine Translation: Shared Task Papers, Oct 2018, Belgium, France. pp.934-938, ⟨10.18653/v1/W18-6485⟩ (2018)
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