哈佛、MIT等机构联合发布论文提出FINSKILLOPS,让智能体从SEC文件分析错误中学习,但每个新行为必须先通过回归测试才能部署。该系统通过小型技能注册表,将重复错误(如用错报告期或混淆公司)转化为可复用指令,仅当新指令修复目标错误且不破坏已有正确行为时才上线,从而把静态RAG系统变为可持续学习并安全更新的金融分析系统。
New Harvard + MIT + other labs paper shows a cleaner path to self-improving financial AI:
let the agent learn from SEC filing errors, but make every new behavior pass regression tests first.
turns SEC-filing analysis from a static RAG system into one that can continuously learn from failures and safely update how it answers.
It turns repeated mistakes into tested skills, and reject any fix that breaks working behavior.
FINSKILLOPS handles this with a small skill registry. Repeated errors, like using the wrong reporting period or mixing companies, become reusable instructions. A new instruction is deployed only if it fixes the target failure and still passes checks on cases the system already answered correctly.
来源:@rohanpaul_ai · x.com