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Abridged primary-source text [2]
Language model agents increasingly act on users' behalf by manipulating external environments through tools, often from high-level instructions that leave critical task- and environment-specific context unstated. To prevent resulting misaligned actions, recent work verifies proposed actions before execution, largely by establishing whether the conditions supporting them hold. We argue that this confirmation-oriented view leaves a fundamental blind spot: a wrong action often passes every check that asks whether it is right.
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- What changed
- The author-supplied record 10.48550/arxiv.2611.02950 makes an abstract and publication details available for “Action Verification through Conjecture and Refutation for Language Model Agents”. [2]