ReasonMed 是目前最大的开源医学推理数据集，相关论文成果为：「ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning」，旨在对医学问答、文本生成等任务的模型进行训练与评估。 该数据集包含 37 万个高质量的问答示例，覆盖临床知识、解剖学、遗传学等多个领域。数据从 3 个大型语言模型（Qwen-2.5-72B 、 DeepSeek-R1-Distill-Llama-70B 和 HuatuoGPT-o1-70B）生成的 175 万条初始推理路径中提取，并经过严格的多智能体验证和优化流程提炼而成。

Citation

@misc{sun2025reasonmed370kmultiagentgenerated,
title={ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning},
author={Yu Sun and Xingyu Qian and Weiwen Xu and Hao Zhang and Chenghao Xiao and Long Li and Yu Rong and Wenbing Huang and Qifeng Bai and Tingyang Xu},
year={2025},
eprint={2506.09513},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2506.09513},
}
@misc{lasateam2025lingshugeneralistfoundationmodel,
title={Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning},
author={LASA Team and Weiwen Xu and Hou Pong Chan and Long Li and Mahani Aljunied and Ruifeng Yuan and Jianyu Wang and Chenghao Xiao and Guizhen Chen and Chaoqun Liu and Zhaodonghui Li and Yu Sun and Junao Shen and Chaojun Wang and Jie Tan and Deli Zhao and Tingyang Xu and Hao Zhang and Yu Rong},
year={2025},
eprint={2506.07044},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2506.07044},
}