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cs.LG2025
PAR-AdvGAN: Improving Adversarial Attack Capability with Progressive Auto-Regression AdvGAN
Jiayu Zhang, Zhiyu Zhu, Xinyi Wang +4
Deep neural networks have demonstrated remarkable performance across various domains. However, they are vulnerable to adversarial examples, which can lead to erroneous predictions.…
cs.LG2024
Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks
Zhibo Jin, Jiayu Zhang, Zhiyu Zhu +3
Adversarial examples are a key method to exploit deep neural networks. Using gradient information, such examples can be generated in an efficient way without altering the victim mo…
cs.LG2024
Enhancing Model Interpretability with Local Attribution over Global Exploration
Zhiyu Zhu, Zhibo Jin, Jiayu Zhang +1
In the field of artificial intelligence, AI models are frequently described as `black boxes' due to the obscurity of their internal mechanisms. It has ignited research interest on…