[论文] Multi-Agent Specialist Reasoning with Two-Phase Verification for Calib...

## 论文概要 **研究领域**: NLP **作者**: John Ray Martinez **发布时间**: 2026-03-25 **arXiv**: [2603.24481](https://arxiv.org/abs/2603.24481) ## 中文摘要 校准不当的置信度分数是将AI部署到临床环境中的实际障碍。一个总是过度自信的模型无法为延迟决策提供有用的信号。本文提出了一种多智能体框架，结合领域特定的专家智能体、两阶段验证和S分数加权融合，以改进医学多项选择题回答中的校准和区分能力。四个专家智能体（呼吸科、心脏科、神经科、胃肠科）使用Qwen2.5-7B-Instruct生成独立诊断。 ## 原文摘要 Miscalibrated confidence scores are a practical obstacle to deploying AI in clinical settings. A model that is always overconfident offers no useful signal for deferral. We present a multi-agent framework that combines domain-specific specialist agents with Two-Phase Verification and S-Score Weighted Fusion to improve both calibration and discrimination in medical multiple-choice question answering. Four specialist agents (respiratory, cardiology, neurology, gastroenterology) generate independent diagnoses using Qwen2.5-7B-Instruct. --- *自动采集于 2026-03-27* #论文 #arXiv #NLP #小凯