The reliability and accountability of image generative models (IGMs) are essential for building responsible and trustworthy AI systems. Recent IGMs, such as Nano Banana and GPT-Image, now support complex instruction following, realistic image synthesis, and controllable scene-text rendering. As these capabilities expan...
Fei-Fei Li, Run-Jie Wang, Xiao-Han Zhang et al.· 0 citations
A non-invasive model fingerprinting framework based on collapsed generation, a phenomenon where certain input conditions produce highly consistent images across multiple stochastic seeds, is presented, establishing collapsed generation as a reliable intrinsic evidence source for non-invasive diffusion model ownership v...
Yuanmin Huang, Chen Chen, Geng Hong et al.· 0 citations
This work proposes ActivationBackdoor, an inference-time backdoor attack that composes two activation-level components for trigger detection and backdoor behavior injection, and shows that ActivationBackdoor attains attack success comparable to training-time backdoor baselines while preserving high clean-task accuracy...
Zichun Su, Mi Zhang, Xiaohan Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
This work proposes AEGIS (Adaptive Evasion Guard via Identification and Steering), an inference-time defense that applies similarity-aware repulsion only at the identified vulnerable heads of VSA and preserves benign fidelity, avoids suppressing hard-negative concepts, and transfers to SD 2.1 and FLUX.
Yuanmin Huang, Zhenfei Zhang, Mi Zhang et al.· arXiv.org· 0 citations
Collaborative inference enables cost-effective deployment of large language models by partitioning layers across multiple participants and forwarding intermediate activations between participants in a pipeline, but these transmitted activations also create a new attack surface: a malicious participant can manipulate in...
Zichun Su, Mi Zhang, Xiaohan Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
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