3 papers
cs.LG2026
Anlu: Enabling In-Context Time Series Anomaly Detection in Foundation Models via Counterfactual Supervision
Tian Lan, Yifei Gao, Yimeng Lu +5
Whether a time-series pattern is anomalous often depends on the operating regime of the monitored process. A missing event can signal a fault in one regime and be routine in anothe…
cs.LG2026
Generalist Representation, Specialist Detection: TS-Router for Time-Series Anomaly Detection
Tian Lan, Yifei Gao, Yimeng Lu +6
Time-series anomaly detection (TSAD) is difficult to generalize across datasets because heterogeneous temporal dynamics imply different notions of normality and favor different det…
cs.AI2026
Supervision Recovery for Time Series Anomaly Detection via Context-Anchored Pairing
Yifei Gao, Tian Lan, Yimeng Lu +5
Time series anomaly detection (TSAD) remains challenging not only because anomaly labels are scarce, but also because temporal anomalies are highly context-dependent. Existing meth…