Papers by Zhongliang Guo

1 papers
P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs (2026.findings-acl)

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Challenge: Defending Large Language Models (LLMs) against backdoors has long been trapped in a "cat-and-mouse" dilemma where defenders passively react to ever-shifting attack strategies.
Approach: They propose a general and effective defense algorithm that implants benign triggers to reshape the model’s decision boundary.
Outcome: The proposed defense algorithm can neutralize malicious backdoors while preserving task performance.

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