Author

Xudong Mou

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#artificial intelligence Preprint Oct 2026

MORA: Modeling Observed Changes for Drift-Robust Time-Series Anomaly Detection

Time-series anomaly detection (TSAD) identifies deviations from patterns learned from historical data. In non-stationary settings, distribution drift and true anomalies can cause similar local changes, making it difficult to tell whether a deviation reflects abnormality or evolving context. Existing methods typically a...

Xu-Dong Mou, Tie-Jun Wang, Rui Wang et al. · 0 citations

Review Aug 2026

Multi-Modal Anomaly Detection: A Survey

This work formalizes the problem, identifies five intrinsic characteristics underlying its core challenges, and organizes prior work into two complementary paradigms, which sharpens decision boundaries through coarse-grained, structural, and semantic anomaly injection.

Xudong Mou, Zexin Wu, Chuan Luo et al. · 0 citations