Simoulin, Antoine, and Benoît Crabbé. Contrasting Distinct Structured Views to Learn Sentence Embeddings In
Proceedings of the 16th {Conference of the {European Chapter of the {Association for {Computational Linguistics: {Student Research Workshop. Online: Association for Computational Linguistics, 2021.
Simoulin, Antoine, and Benoît Crabbé. How Many Layers and Why? An Analysis of the Model Depth in Transformers In
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop. Online: Association for Computational Linguistics, 2021.
Simoulin, Antoine, and Benoît Crabbé. Un modèle Transformer Génératif Pré-entrainé pour le ______ français In
Traitement Automatique des Langues Naturelles, Edited by
Pascal Denis,
Natalia Grabar,
Amel Fraisse,
Rémi Cardon,
Bernard Jacquemin,
Eric Kergosien and
Antonio Balvet. Lille, France: ATALA, 2021.
Simoulin, Antoine, and Benoît Crabbé. Unifying Parsing and Tree-Structured Models for Generating Sentence Semantic Representations In
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop. Hybrid: Seattle, Washington + Online: Association for Computational Linguistics, 2022.