斯坦福与牛津的 MedRSI 论文显示,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病例上验证通过才能固化。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);放慢注册节奏后仅保留 18 个工具,准确率维持 94.4%。该智能体还会优先投入可能造成更大临床危害的错误,而非仅处理最常见错误。
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:@rohanpaul_ai · x.com