Papers by Sibei Yang

2 papers
DELMAN: Dynamic Defense Against Large Language Model Jailbreaking with Model Editing (2025.findings-acl)

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Challenge: Existing safety mechanisms for Large Language Models (LLMs) are inadequate to protect against jailbreak attacks, resulting in performance degradation on general tasks.
Approach: They propose a method that directly updates a minimal set of relevant parameters to neutralize harmful behaviors while preserving the model’s utility.
Outcome: The proposed model outperforms baseline methods in mitigating jailbreak attacks while preserving the model’s utility.
Don’t Say No: Jailbreaking LLM by Suppressing Refusal (2025.findings-acl)

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Challenge: Large Language Models (LLMs) are vulnerable to "jailbreaking" attacks where crafted prompts manipulate them into producing toxic content.
Approach: They propose to improve the target loss objective by combining a cosine decay schedule method with refusal suppression to achieve higher success rates.
Outcome: The proposed approach outperforms baseline attacks and achieves state-of-the-art attack success rates.

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