$R^3$: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent System for Text-to-SQL Tasks
<|reference_start|>$R^3$: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent System for Text-to-SQL Tasks: Large Language Models (LLMs) have demonstrated strong performance on various tasks. To unleash their power on the Text-to-SQL task, we propose $R^3$ (Review-Rebuttal-Revision), a consensus-based multi-agent system for Text-to-SQL tasks. $R^3$ outperforms the existing single LLM Text-to-SQL systems as well as the multi-agent Text-to-SQL systems by $1.3\%$ to $8.1\%$ on Spider and Bird. Surprisingly, we find that for Llama-3-8B, $R^3$ outperforms chain-of-thought prompting by over 20\%, even outperforming GPT-3.5 on the development set of Spider.<|reference_end|>
@article{xia2024$r^3$:,
    title={$R^3$: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent
  System for Text-to-SQL Tasks},
    author={Hanchen Xia, Feng Jiang, Naihao Deng, Cunxiang Wang, Guojiang Zhao,
  Rada Mihalcea, and Yue Zhang},
    journal={arXiv preprint arXiv:2402.14851},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.14851},
    primaryClass={cs.CL cs.AI cs.DB}
}