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cs.CR2025
Probe before You Talk: Towards Black-box Defense against Backdoor Unalignment for Large Language Models
Biao Yi, Tiansheng Huang, Sishuo Chen +4
Backdoor unalignment attacks against Large Language Models (LLMs) enable the stealthy compromise of safety alignment using a hidden trigger while evading normal safety auditing. Th…
cs.CR2024
When Backdoors Speak: Understanding LLM Backdoor Attacks Through Model-Generated Explanations
Huaizhi Ge, Yiming Li, Qifan Wang +2
Large Language Models (LLMs) are known to be vulnerable to backdoor attacks, where triggers embedded in poisoned samples can maliciously alter LLMs' behaviors. In this paper, we mo…
cs.CR2024
BadActs: A Universal Backdoor Defense in the Activation Space
Biao Yi, Sishuo Chen, Yiming Li +3
Backdoor attacks pose an increasingly severe security threat to Deep Neural Networks (DNNs) during their development stage. In response, backdoor sample purification has emerged as…