3 papers
cs.LG2026
Poisoning the Inner Prediction Logic of Graph Neural Networks for Clean-Label Backdoor Attacks
Yuxiang Zhang, Bin Ma, Enyan Dai
Graph Neural Networks (GNNs) have achieved remarkable results in various tasks. Recent studies reveal that graph backdoor attacks can poison the GNN model to predict test nodes wit…
cs.LG2026
SCL-GNN: Towards Generalizable Graph Neural Networks via Spurious Correlation Learning
Yuxiang Zhang, Enyan Dai
Graph Neural Networks (GNNs) have demonstrated remarkable success across diverse tasks. However, their generalization capability is often hindered by spurious correlations between…
cs.LG2024
Disttack: Graph Adversarial Attacks Toward Distributed GNN Training
Yuxiang Zhang, Xin Liu, Meng Wu +4
Graph Neural Networks (GNNs) have emerged as potent models for graph learning. Distributing the training process across multiple computing nodes is the most promising solution to a…