Author of the publication

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

Generating Artificial Texts as Substitution or Complement of Training Data., , and . LREC, page 4260-4269. European Language Resources Association, (2022)Three Bricks to Consolidate Watermarks for Large Language Models., , , , and . WIFS, page 1-6. IEEE, (2023)La génération de textes artificiels en substitution ou en complément de données d'apprentissage (Generating artificial texts as substitution or complement of training data )., , and . TALN (1), page 37-49. ATALA, (2021)Which Discriminator for Cooperative Text Generation?, , , , , , and . SIGIR, page 2360-2365. ACM, (2022)"Honey, Tell Me What's Wrong", Explicabilité Globale des Modèles de TAL par la Génération Coopérative., and . CORIA-TALN (1), page 105-122. ATALA, (2023)Multitask Prompted Training Enables Zero-Shot Task Generalization, , , , , , , , , and 30 other author(s). International Conference on Learning Representations, (2022)Décodage guidé par un discriminateur avec le Monte Carlo Tree Search pour la génération de texte contrainte (Discriminator-guided decoding with Monte Carlo Tree Search for constrained text generation )., , and . TALN-RECITAL, page 27-41. ATALA, (2022)Generative Cooperative Networks for Natural Language Generation., , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 11891-11905. PMLR, (2022)"Honey, Tell Me What's Wrong", Global Explanation of Textual Discriminative Models through Cooperative Generation., and . BlackboxNLP@EMNLP, page 76-88. Association for Computational Linguistics, (2023)Multimodal misinformation detection overcoming the training data collection challenge through data generation. (Détection de désinformation multimodale : surmonter le défi de la collecte de données d'entraînement grâce à la génération de données).. University of Rennes 1, France, (2023)