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Training Advisors for LLM Agents from Task Outcomes

Polezhaev, Sergei et al.
arXiv (All) · Papers
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computation-and-language
Large language model agents tackle multi-step tasks by interleaving reasoning and tool calls with observations from the environment. Prior work has shown that natural-language feedback can help these agents revise their decisions during task execution. We introduce Caddie, a method for training crit
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