TA-GGAD: Testing-time Adaptive Graph Model for Generalist Graph Anomaly Detection

ArXi:2603.09349v1 Announce Type: cross A significant number of anomalous nodes in the real world, such as fake news, noncompliant users, malicious transactions, and malicious posts, severely compromises the health of the graph data ecosystem and urgently requires effective identification and processing. With anomalies that span multiple data domains yet exhibit vast differences in features, cross-domain detection models face severe domain shift issues, which limit their generalizability across all domains.