Author

Jun-Hua Liu

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#artificial intelligence Preprint Sep 2026

Bait-and-Recover: Poisoning Internal Refusal Signals to Defend LLMs against White-Box Editing Jailbreaks

Bait-and-Recover is proposed, a weight-level defense that places a bait adapter where attackers read activations and a paired recovery adapter at the subsequent layer that decouples the observation path from the behavior path.

Tian Gao, Zhi-Hui Xie, Yu-Hao Wu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Who Judges the Judges? A Chinese Safety QA Benchmark for Evaluating LLM Responses and Safety Judges

C-SafeQA, a policy-grounded benchmark for response-level Chinese safety evaluation, is introduced, with substantial trade-offs between unsafe-response recall and risk-query-conditioned safe-response false positive rate.

Rui-Wei-Chun-Hui-Li-Yuan Yang, Shuang Huang, Jun-Hua Liu et al. · 0 citations