Papers by Shuaibiao Han

2 papers
Dictionary Guided Sparse Logit Editing for Reliable Jailbreak Attacks (2026.findings-acl)

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Challenge: Existing methods to optimize large language models suffer from high computational costs and produce uninterpretable, high-perplexity inputs.
Approach: They propose a sparse index-based intervention that bypasses guardrails via sparser logit editing.
Outcome: The proposed method bypasses guardrails by modifying pre-softmax logits without gradients or auxiliary models.
Defending LLMs against Jailbreak Attacks via Template-Based ICL with a Defensive Suffix (2026.findings-acl)

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Challenge: State-of-the-art large language models (LLMs) are vulnerable to jailbreak attacks, such as GCG and AutoDAN.
Approach: They propose to take the advances of online In-Context Learning and an offline defensive suffix and optimize them using an iterative algorithm and an online stochastic random search to identify the most effective ICL demonstrations.
Outcome: The proposed method reduces attack success rate to nearly *0% while maintaining the model’s utility on benign tasks and incurring only *negligible* computational overhead.

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