5 papers
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…
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…
FairGE: Fairness-Aware Graph Encoding in Incomplete Social Networks
Renqiang Luo, Huafei Huang, Tao Tang +5
Graph Transformers (GTs) are increasingly applied to social network analysis, yet their deployment is often constrained by fairness concerns. This issue is particularly critical in…
Let's Grow an Unbiased Community: Guiding the Fairness of Graphs via New Links
Jiahua Lu, Huaxiao Liu, Shuotong Bai +3
Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications. However, due to the biases in the graph structures, graph neural networks face significan…
Fairness in Augmented Graph Learning: A Survey
Renqiang Luo, Ziqi Xu, Xikun Zhang +6
Graph learning has evolved into Augmented Graph Learning (AGL) by integrating specialized machine learning (ML) techniques. Examples include federated learning, graph transformers,…