Generating Task-Specific Actions in Large Language Models

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Machine Learning

Artificial Intelligence

Computation and Language

Generating Task-Specific Actions in Large Language Models

ReAct: Synergizing Reasoning and Acting in Language Models

Large language models (llm) have demonstrated impressive capabilitiesacross tasks in language understanding and interactive decision making, but their abilities for reasoning (e.g.

Chain-of-thought prompting) and acting (e.g.action plan generation) have primarily been studied as separate topics.

We apply our approach, named react, to a diverse set of language and decision making tasks and demonstrate its effectiveness over state-of-the-art baselines, as well as improved human interpretability and trustworthiness over methods without reasoning or acting components.

Authors

Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, Yuan Cao

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