10 papers
Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment
Mathieu Petitbois, Rémy Portelas, Sylvain Lamprier
We study offline reinforcement learning of style-conditioned policies using explicit style supervision via subtrajectory labeling functions. In this setting, aligning style with hi…
Agentic Adversarial QA for Improving Domain-Specific LLMs
Vincent Grari, Ciprian Tomoiaga, Sylvain Lamprier +2
Large Language Models (LLMs), despite extensive pretraining on broad internet corpora, often struggle to adapt effectively to specialized domains. There is growing interest in fine…
SAC-GLAM: Improving Online RL for LLM agents with Soft Actor-Critic and Hindsight Relabeling
Loris Gaven, Clement Romac, Thomas Carta +3
The past years have seen Large Language Models (LLMs) strive not only as generative models but also as agents solving textual sequential decision-making tasks. When facing complex…
Imagine Beyond! Distributionally Robust Auto-Encoding for State Space Coverage in Online Reinforcement Learning
Nicolas Castanet, Olivier Sigaud, Sylvain Lamprier
Goal-Conditioned Reinforcement Learning (GCRL) enables agents to autonomously acquire diverse behaviors, but faces major challenges in visual environments due to high-dimensional,…
A Transformer Model for Predicting Chemical Products from Generic SMARTS Templates with Data Augmentation
Derin Ozer, Sylvain Lamprier, Thomas Cauchy +2
The accurate prediction of chemical reaction outcomes is a major challenge in computational chemistry. Current models rely heavily on either highly specific reaction templates or t…
Reinforcement Learning for Aligning Large Language Models Agents with Interactive Environments: Quantifying and Mitigating Prompt Overfitting
Mohamed Salim Aissi, Clement Romac, Thomas Carta +5
Reinforcement learning (RL) is a promising approach for aligning large language models (LLMs) knowledge with sequential decision-making tasks. However, few studies have thoroughly…