Hui-Ling Peng

Capturing Collaborative Structure in Graph Anomaly Detection by MoE-Gated Neural Common Neighbor

In real-world graphs, anomalies usually exhibit collaborative structure, manifested as densely connected sub-graphs. Capturing multi-hop relationships is essential to identify and characterize the connections among these anomalous nodes. Existing graph anomaly detection (GAD) methods fail to capture such structures due...