Preprint
Aug 2026
CARE: A Cascaded Framework for Efficient and Reliable Time Series Anomaly Detection
CARE, a model-agnostic cascaded inference framework that integrates a Lightweight Pre-filter Model (LPM) with an existing high-capacity Complex Detection Model (CDM) and introduces a Structure Attention module to explicitly capture channel-wise anomaly contributions, achieves inference speedup compared to the most accurate SOTA approaches.
Zemin Chao, Qian Xu, Jian-He Cen et al.
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