5 citations · 9 across the 8 of their papers we have counts for
4 papers · 1 filter
Zero-Shot End-To-End Spoken Question Answering In Medical Domain
Yanis Labrak, Adel Moumen, Richard Dufour +1
In the rapidly evolving landscape of spoken question-answering (SQA), the integration of large language models (LLMs) has emerged as a transformative development. Conventional appr…
DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical domains
Yanis Labrak, Adrien Bazoge, Richard Dufour +4
In recent years, pre-trained language models (PLMs) achieve the best performance on a wide range of natural language processing (NLP) tasks. While the first models were trained on…
FrenchMedMCQA: A French Multiple-Choice Question Answering Dataset for Medical domain
Yanis Labrak, Adrien Bazoge, Richard Dufour +4
This paper introduces FrenchMedMCQA, the first publicly available Multiple-Choice Question Answering (MCQA) dataset in French for medical domain. It is composed of 3,105 questions…
Building a robust sentiment lexicon with (almost) no resource
Mickael Rouvier, Benoit Favre
Creating sentiment polarity lexicons is labor intensive. Automatically translating them from resourceful languages requires in-domain machine translation systems, which rely on lar…