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VLGOR: Visual-Language Knowledge Guided Offline Reinforcement Learning for Generalizable Agents

Description

Combining Large Language Models (LLMs) with Reinforcement Learning (RL) enables agents to interpret language instructions more effectively for task execution. However, LLMs typically lack direct perception of the physical environment, which limits their understanding of environmental dynamics and their ability to generalize to unseen tasks. To address this limitation, we propose Visual-Language Knowledge-Guided Offline Reinforcement Learning (VLGOR), a framework that integrates visual and langua

Source

http://arxiv.org/abs/2603.22892v1