Constructing and Evaluating Clinical Reasoning Trajectories for Medical Agent

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A paper published on September 7, 2026, on arXiv cs.AI, titled “Constructing and Evaluating Clinical Reasoning Trajectories for Medical Agents,” aims to build and evaluate the clinical reasoning trajectories of medical agents.

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CECMedCareQAMedTrajPubMedQA

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MedTraj1
CareQA1
PubMedQA1
CECMed1

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A arXiv cs.AI en 2026-09-07 12:00

研究人员提出 MedTraj 框架，旨在解决医疗人工智能评估仅关注最终答案而忽视推理过程质量的问题。该框架将推理轨迹视为关键对象进行构建、评估与优化，通过解析临床观察、证据及步骤生成结构化多步推理链，并从连贯性、证据支持度等五个维度进行评分。实验在 CareQA、PubMedQA 和 CECMed 数据集上验证了该方法的有效性，结果显示轨迹上下文使推理连贯性提升 0.029 至 0.041；在 CECMed 上，质量加权上下文将正确率几乎翻倍，幻觉比例降低 87%。此外，边际贡献分析表明少数关键步骤承载主要质量信号，且超过四步后收益递减。