AI RESEARCH
OWLEYE: Zero-Shot Learner for Cross-Domain Graph Data Anomaly Detection
arXiv CS.LG
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ArXi:2601.19102v2 Announce Type: replace Graph data is informative to represent complex relationships such as transactions between accounts, communications between devices, and dependencies among machines or processes. Correspondingly, graph anomaly detection (GAD) plays a critical role in identifying anomalies across various domains, including finance, cybersecurity, manufacturing, etc. Facing the large-volume and multi-domain graph data, nascent efforts attempt to develop foundational generalist models capable of detecting anomalies in unseen graphs without re.