Few-shot Pseudo-Labeling for Intent Detection. - Thomas Dopierre; Christophe Gravier; Julien Subercaze; Wilfried Logerais (COLING, 2020)

ProtAugment: Intent Detection Meta-Learning through Unsupervised Diverse Paraphrasing. - Thomas Dopierre; Christophe Gravier; Wilfried Logerais (ACL/IJCNLP (1), 2021)

A Neural Few-Shot Text Classification Reality Check. - Thomas Dopierre; Christophe Gravier; Wilfried Logerais (EACL, 2021)

ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learning. - Thomas Dopierre; Christophe Gravier; Wilfried Logerais (CoRR, 2021)

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation. - Kaustubh D. Dhole; Varun Gangal; Sebastian Gehrmann; Aadesh Gupta; Zhenhao Li; Saad Mahamood; Abinaya Mahendiran; Simon Mille; Ashish Srivastava; Samson Tan; Tongshuang Wu; Jascha Sohl-Dickstein; et al. (CoRR, 2021)

Few-Shot Intent Classification in User-Generated Short Texts: Application to Conversational Agents. (Classification d'intentions de requêtes générées par utilisateurs en régime «few-shot»: Application aux agents conversationnels). - Thomas Dopierre (2021)