1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2025
Boosting Generative Adversarial Transferability with Self-supervised Vision Transformer Features
Shangbo Wu, Yu-an Tan, Ruinan Ma +3
The ability of deep neural networks (DNNs) come from extracting and interpreting features from the data provided. By exploiting intermediate features in DNNs instead of relying on…
cs.LG2022★ 1 cited
l-Leaks: Membership Inference Attacks with Logits
Shuhao Li, Yajie Wang, Yuanzhang Li +1
Machine Learning (ML) has made unprecedented progress in the past several decades. However, due to the memorability of the training data, ML is susceptible to various attacks, espe…
cs.CV2022
Improving the Transferability of Adversarial Examples with Restructure Embedded Patches
Huipeng Zhou, Yu-an Tan, Yajie Wang +3
Vision transformers (ViTs) have demonstrated impressive performance in various computer vision tasks. However, the adversarial examples generated by ViTs are challenging to transfe…