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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Author

Yingxuan Li

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Book Open access Aug 2026

Mitigating Anomaly Hallucination: A Model-Agnostic Framework for Unsupervised Anomaly Detection on Dynamic Graphs

The proposed AHEAD, an unsupervised anti-hallucination anomaly detection framework featuring a hallucination refinement pipeline and a temporal-structural detector, which is compatible with various T-GNN backbones for reliable anomaly detection on CTDGs.

Yingxuan Li, Yuanyuan Xu, Xue-Min Lin et al. · 0 citations
Book Aug 2026

Mitigating Anomaly Hallucination: A Model-Agnostic Framework for Unsupervised Anomaly Detection on Dynamic Graphs

Temporal graph neural networks (T-GNNs) are powerful for representation learning on continuous-time dynamic graphs (CTDGs), but naively applying them to unsupervised anomaly detection is often unreliable. The key challenge is learning normal dynamics while being exposed to unlabeled anomalies, which destabilizes optimi...

Yingxuan Li, Yuanyuan Xu, Xuemin Lin et al. · 0 citations

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