Concept erasure aims to suppress undesirable knowledge in text-to-image generative models. However, existing robustness evaluations typically rely on relearning attacks tailored to specific model architectures. We study concept reactivation across two substantially different generative paradigms: noise-prediction U-Net...
Hong Xi Tae, Jia-Ming Zhang, Wen-Wen He et al.· 0 citations
This survey examines the protective paradigm that has grown around this intervention point, and finds that most protections are still validated mainly against static or weakly adaptive adversaries, while evidence beyond controlled benchmarks remains scarce.
Jiaming Zhang, Bo-Yang Chen, Zhe-Rui Li et al.· 0 citations
DecisionQE is introduced, a questionnaire-based framework for measuring each model's persuasive and compliant tendencies across multiple decision scenarios, and the Werewolf game is used as an interactive testbed to study their effects on social influence and group outcomes under asymmetric information.
Wen-Wen He, Wen-Ke Huang, Wei Yang Bryan Lim et al.· 0 citations
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