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cs.CR2026
AMRM-Pure: Semantic-Preserving Adversarial Purification
Zhihao Dou, Zhiqiang Gao, Dongfei Cui +6
Adversarial purification is a defense technique that employs generative models to remove adversarial perturbations. Current methods often rely on powerful generators, typically dif…
cs.CR2026
ReShift: Aha-Moment-Driven Reasoning-Level Backdoor Attacks on Vision-Language Models
Zhihao Dou, Qinjian Zhao, Zhiqiang Gao +1
Vision--Language Models (VLMs) are increasingly deployed in safety-critical applications, yet remain vulnerable to backdoor attacks. Existing methods primarily manipulate final out…
cs.CR2026
ProtoGuard-SL: Prototype Consistency Based Backdoor Defense for Vertical Split Learning
Yuhan Shui, Ruobin Jin, Zhihao Dou +1
Vertical split learning (SL) enables collaborative model training across parties holding complementary features without sharing raw data, but recent work has shown that it is highl…