4 papers
Whatever Remains Must Be True: Filtering Drives Reasoning in LLMs, Shaping Diversity
Germán Kruszewski, Pierre Erbacher, Jos Rozen +1
Reinforcement Learning (RL) has become the de facto standard for tuning LLMs to solve tasks involving reasoning. However, growing evidence shows that models trained in such way oft…
FaST: Feature-aware Sampling and Tuning for Personalized Preference Alignment with Limited Data
Thibaut Thonet, Germán Kruszewski, Jos Rozen +2
LLM-powered conversational assistants are often deployed in a one-size-fits-all manner, which fails to accommodate individual user preferences. Recently, LLM personalization -- tai…
Guaranteed Generation from Large Language Models
Minbeom Kim, Thibaut Thonet, Jos Rozen +3
As large language models (LLMs) are increasingly used across various applications, there is a growing need to control text generation to satisfy specific constraints or requirement…
ELITR-Bench: A Meeting Assistant Benchmark for Long-Context Language Models
Thibaut Thonet, Jos Rozen, Laurent Besacier
Research on Large Language Models (LLMs) has recently witnessed an increasing interest in extending the models' context size to better capture dependencies within long documents. W…