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ENTITY Refuse without Refusal: A Structural Analysis of Safety-Tuning Responses for Reducing False Refusals in Language Models

Refuse without Refusal: A Structural Analysis of Safety-Tuning Responses for Reducing False Refusals in Language Models

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  1. TOOL · CL_239302 ·

    AI safety tuning: Rationales reduce false refusals, improve helpfulness

    Researchers have identified a key issue in the safety tuning of large language models: boilerplate refusal statements can lead to false refusals by causing models to rely on superficial cues. By decomposing responses in…