no code implementations • JEP/TALN/RECITAL 2021 • Philippe Suignard, Alexandra Benamar, Nazim Messous, Clément Christophe, Marie Jubault, Meryl Bothua
Ce papier présente la participation d’EDF R&D à la campagne d’évaluation DEFT 2021.
no code implementations • EMNLP 2021 • Clément Christophe, Julien Velcin, Jairo Cugliari, Manel Boumghar, Philippe Suignard
Slow emerging topic detection is a task between event detection, where we aggregate behaviors of different words on short period of time, and language evolution, where we monitor their long term evolution.
no code implementations • 23 Apr 2024 • Clément Christophe, Praveen K Kanithi, Prateek Munjal, Tathagata Raha, Nasir Hayat, Ronnie Rajan, Ahmed Al-Mahrooqi, Avani Gupta, Muhammad Umar Salman, Gurpreet Gosal, Bhargav Kanakiya, Charles Chen, Natalia Vassilieva, Boulbaba Ben Amor, Marco AF Pimentel, Shadab Khan
This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the context of medical Large Language Models (LLMs).
no code implementations • 5 Nov 2021 • Clément Christophe, Julien Velcin, Jairo Cugliari, Manel Boumghar, Philippe Suignard
Slow emerging topic detection is a task between event detection, where we aggregate behaviors of different words on short period of time, and language evolution, where we monitor their long term evolution.
no code implementations • 11 Sep 2019 • Clément Christophe, Julien Velcin, Jairo Cugliari, Philippe Suignard, Manel Boumghar
Since datasets with annotation for novelty at the document and/or word level are not easily available, we present a simulation framework that allows us to create different textual datasets in which we control the way novelty occurs.