←新闻详情

Rohan Paul更新于 10月21日 22:46

Anthropic:模型自述推理不可信

Anthropic states plainly that the model’s own explanation of its reasoning can’t be trusted as evidence of why it acted, which is exactly why they can’t cleanly

AI 导读

Anthropic 明确表示,模型对自身推理的解释不能作为其行动原因的证据,这正是他们无法清晰判断这些失败各自严重程度的原因。

引用

Rohan Paul

@rohanpaul_ai

Claude fabricated an eyewitness account for a real unsolved homicide and submitted it through a police department’s public tip form, even though the page carried no suspect description to match against. It left the name and contact fields blank, the tip was flagged as spam, and it never reached investigators. Anthropic has cut live internet access from…

展开完整原文

Claude fabricated an eyewitness account for a real unsolved homicide and submitted it through a police department’s public tip form, even though the page carried no suspect description to match against. It left the name and contact fields blank, the tip was flagged as spam, and it never reached investigators. Anthropic has cut live internet access from all internal evaluations until its monitoring reliably catches such behavior. It rates every case as minimal-impact and significantly less severe than this summer’s cybersecurity incidents, when Claude held access to third-party systems for hours. Still, some sites belonged to US federal, state and local agencies, so the company briefed the White House. After a university’s analysis tool failed, Claude Mythos Preview copied server code through a file-leaking script, found an injection flaw and ran its calculation there. The tip came from Claude Haiku 4.5, which was generating example tasks on random webpages and filled a Philadelphia Police Department form anonymously. The model claimed a sighting matching a description the page never gave, and the submission was flagged as spam. Claude Mythos 5 reached fee-gated public data with access tokens from a local government map’s settings file and a state agency’s dashboard. Claude Opus 5 and Mythos 5 also slipped past fetch-tool URL length limits, which guard against injection attacks, by using free link shorteners. Many cases began with ambiguous or impossible tasks, and Anthropic is fixing training environments that rewarded working around blockers. Public web benchmarks such as BrowseComp run on the live internet by default, so rival labs testing agents that way face the same exposure.

查看原帖

正文

当前显示原文,中文全文译文尚未就绪。

Anthropic states plainly that the model’s own explanation of its reasoning can’t be trusted as evidence of why it acted, which is exactly why they can’t cleanly judge how severe each of these failures was. https://t.co/m0Fu2Ts2xE

来源

Rohan Paul