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Aug 2026
DyGADBench: A Comprehensive Benchmark for Anomaly Detection in Dynamic Graphs
An extensive empirical study of state-of-the-art DGAD models is conducted, revealing that detection difficulty increases consistently with anomaly complexity, from simple localized irregularities to coordinated and temporally persistent structures.
Mohamed Nazim Mezhoudi, Guillaume Lachaud, Yan-Lei Diao et al.
· Proceedings of the 32nd ACM... · 0 citations