Papers by Shipeng Wang

1 papers
SAME: Safety-Aware Model Editing Guided by Safety Transformation (2026.acl-long)

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Challenge: Existing models that update or insert new knowledge require sequential parameter updates while maintaining model capability.
Approach: They propose a model editing approach that estimates safety transforms and identifies corresponding safety direction in the neural activation space and aligns neural activations and network parameter updates under the safety constraints.
Outcome: The proposed approach reduces unsafe responses to malicious queries while preserving the effectiveness of model editing.

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