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Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF Verbalization with Transformers.

, , , , and . CoRR, (2020)

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aceMedia: Knowledge-based Semantic Annotation and Retrieval of Multimedia Content, , , , , , and . Proceedings of MAReSO Workshop 2007, (2007)Discourse Representation Theory et graphes sémantiques : formalisation sémantique en contexte industriel., , and . TALN (Articles courts), page 41-50. ATALA, (2008)Génération automatique des représentations ontologiques.. TALN (Posters), page 502-511. ATALA, (2006)Approche de génération de réponse à base de transformers (Transformer based approach for answer generation)., , and . JEP-TALN-RECITAL (2), page 2-11. ATALA et AFCP, (2020)Multimedia Reasoning with Natural Language Support., , , and . ICSC, page 413-420. IEEE Computer Society, (2007)Interprétation linguistique de requêtes pour un moteur de questions réponses grand public., and . CORIA, page 207-214. Éditions Universitaires d'Avignon, (2011)CALOR-QUEST : generating a training corpus for Machine Reading Comprehension models from shallow semantic annotations., , , , , , and . MRQA@EMNLP, page 19-26. Association for Computational Linguistics, (2019)MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging., , and . SemEval@NAACL-HLT, page 107-112. Association for Computational Linguistics, (2019)Étiquetage ou génération de séquences pour la compréhension automatique du langage en contexte d'interaction? (Sequence tagging or sequence generation for Natural Language Understanding ?)., , , and . TALN-RECITAL, page 64-73. ATALA, (2022)CALOR-QUEST : un corpus d'entraînement et d'évaluation pour la compréhension automatique de textes (Machine reading comprehension is a task related to Question-Answering where questions are not generic in scope but are related to a particular document)., , , , , , and . PFIA (Articles courts), page 185-194. ATALA, (2019)