french

This paper introduces a French OSCE dialogue dataset of 240 interactions and a controllable LLM-based pipeline for generating synthetic OSCE dialogues, enabling realistic virtual patient simulations for medical training with automatic feedback.

This paper compares the geometric structures induced by deep learning vector embeddings (CamemBERT) and lexical co-occurrence graph models on the French 'Great National Debate' corpus, finding similar local topology but distinct global organization, highlighting complementarity between the two approaches.

Describes the conversion of French verb Lexicon-Grammar tables into the LMF format, enhancing interoperability and standardization for NLP dictionaries.