Papers with lightweight training-based approach

1 papers
You Only Need One Single Token to Refine Safety Alignment (2026.findings-acl)

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Challenge: Excessive safety can lead to over-refusal, where models reject harmful-looking yet benign queries, severely limiting utility.
Approach: They propose a lightweight training-based approach that reshapes the distributions of harmful and benign samples within the model’s decision space by using a single-token prefix.
Outcome: The proposed approach can distinguish between harmful and benign samples while keeping the model frozen.

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