ReAct: Synergizing Reasoning and Acting in Language Models

Abstract

Interleaves verbal reasoning traces with tool actions, so the model thinks about what to do next, does it, then reasons about what came back. The reasoning trace also becomes an auditable record of why the agent took each step.

@inproceedings{yao2022react,
  author    = {Shunyu Yao and Jeffrey Zhao and Dian Yu and Nan Du and Izhak Shafran and Karthik Narasimhan and Yuan Cao},
  title     = {ReAct: Synergizing Reasoning and Acting in Language Models},
  booktitle = {International Conference on Learning Representations (ICLR) 2023},
  year      = {2022},
  eprint    = {2210.03629},
  archivePrefix = {arXiv},
  url       = {https://arxiv.org/abs/2210.03629}
}