Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate

Summary

arXiv:2606.02670v1 Announce Type: new Abstract: Many recent multivariate time series anomaly detection (MT-SAD) models incorporate cross-channel modeling, under the implicit assumption that the structure of anomalies may be spread across multiple channels. We evaluate this assumption on eight widely used public benchmarks by introducing a per-segment diagnostic framework that flags, for each labeled anomaly, whether at least one channel deviates individually from its normal history, whether the cross-channel correlation structure changes, or both. The framework shows that no crosschannel rupture occurs without an accompanying univariate deviation across a range of reasonable thresholds.