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Self-Attribution Bias: When AI Monitors Go Easy on Themselves

AI & ML·2 min read·via ArXivOriginal source →

Self-Attribution Bias: When AI Monitors Go Easy on Themselves

arXiv:2603.04582v1 Announce Type: new Abstract: Agentic systems increasingly rely on language models to monitor their own behavior. For example, coding agents may self critique generated code for pull request approval or assess the safety of tool-use actions. We show that this design pattern can fail when the action is presented in a previous or in the same assistant turn instead of being presented by the user in a user turn. We define self-attribution bias as the tendency of a model to evaluat

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