斯坦福牛津 MedRSI:医疗智能体自我改进需护栏

Rohan Paul · @rohanpaul_ai · X·2026-09-23 11:27·2小时前
AI 导读

斯坦福与牛津论文 MedRSI 显示,医疗智能体可从自身错误中自我改进,但新能力须先在后续新患者上验证才能固化。若每轮都立即注册新工具,第 30 轮准确率降至 76.9%(57 个工具);放慢注册、仅保留 18 个工具时准确率达 94.4%。该智能体还会优先处理可能造成更大临床危害的错误,而非仅关注最常见错误。

Rohan Paul@rohanpaul_ai
45AI 编辑部评分,满分 100

斯坦福牛津 MedRSI:医疗智能体自我改进需护栏

2026-09-23 11:27· 2小时前
AI 导读

斯坦福与牛津论文 MedRSI 显示,医疗智能体可从自身错误中自我改进,但新能力须先在后续新患者上验证才能固化。若每轮都立即注册新工具,第 30 轮准确率降至 76.9%(57 个工具);放慢注册、仅保留 18 个工具时准确率达 94.4%。该智能体还会优先处理可能造成更大临床危害的错误,而非仅关注最常见错误。

New Stanford+Oxford paper MedRSI shows that medical agents can improve themselves from their own mistakes, but only if new capabilities are tested on fresh patients before becoming permanent.

shows self-improving agents need 2 things: focus on harmful failures and refuse to keep new capabilities until they work on later cases.

More important, the paper shows why self-improvement needs guardrails.

If every promising tool is added immediately, accuracy eventually falls: 76.9% by round 30 with 57 tools.

With slower registration, the agent kept just 18 tools and held 94.4%.

It also spends more effort on mistakes that could cause greater clinical harm, rather than just the most common errors.

let agents invent aggressively, but make permanent self-changes earn their place through repeated independent evaluation.

来源:Rohan Paul· x.com