Author

Hong Xi Tae

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Preprint Sep 2026

Concept Score Relearning: A Unified Cross-Architecture Attack on Concept Erasure

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

#artificial intelligence Review May 2026

FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

FraudBench is a multimodal benchmark for detecting AI-generated fraudulent refund evidence and shows that current MLLMs often recognize real-damaged evidence but fail on many fake-damaged subsets, with fake-damage detection rates far below the 50\% baseline on most generator subsets.

Xinyu Yan, Bo-Yang Chen, Jia-Ming Zhang et al. · arXiv.org · 1 citation

Review Aug 2026

Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle

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