Dual spatial-temporal attribution for architecture-aligned post-hoc explainability in recurrent graph anomaly detection
Read the original at arxiv.org→arXiv:2608.12441v1 Announce Type: new Abstract: Deep learning detectors for anomalies in dynamic graphs have reached strong accuracy, yet they remain opaque: when an edge is flagged, the analyst receives a score but...
Original headline: "Dual Spatial-Temporal Attribution: Architecture-Aligned Post-Hoc Explainability for Recurrent Graph Anomaly Detection"
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- Aug 14, 04:00 UTC arXiv cs.LG lead source Dual Spatial-Temporal Attribution: Architecture-Aligned Post-Hoc Explainability for Recurrent Graph Anomaly Detection