AutoGuide introduces a framework to extract state-aware guidelines from offline data, improving LLM agents' decision-making. By leveraging implicit knowledge in offline experiences, AutoGuide provides concise natural language guidelines that enhance an agent's performance. The method outperforms competitive baselines in sequential decision-making benchmarks by providing relevant guidelines at test time based on the current state.
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by Yao Fu,Dong-... at arxiv.org 03-15-2024
https://arxiv.org/pdf/2403.08978.pdfDeeper Inquiries