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cs.LG2024
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…
cs.LG2024
Physics-Informed Model and Hybrid Planning for Efficient Dyna-Style Reinforcement Learning
Zakariae El Asri, Olivier Sigaud, Nicolas Thome
Applying reinforcement learning (RL) to real-world applications requires addressing a trade-off between asymptotic performance, sample efficiency, and inference time. In this work,…