1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2025
Less Is More: Sparse and Cooperative Perturbation for Point Cloud Attacks
Keke Tang, Tianyu Hao, Xiaofei Wang +4
Most adversarial attacks on point clouds perturb a large number of points, causing widespread geometric changes and limiting applicability in real-world scenarios. While recent wor…
cs.LG2024★ 1 cited
A General Black-box Adversarial Attack on Graph-based Fake News Detectors
Peican Zhu, Zechen Pan, Yang Liu +3
Graph Neural Network (GNN)-based fake news detectors apply various methods to construct graphs, aiming to learn distinctive news embeddings for classification. Since the constructi…
cs.LG2023
Advancing Adversarial Robustness Through Adversarial Logit Update
Hao Xuan, Peican Zhu, Xingyu Li
Deep Neural Networks are susceptible to adversarial perturbations. Adversarial training and adversarial purification are among the most widely recognized defense strategies. Althou…