ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection 事件

ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection arXiv:2606.01300v1 Announce Type: cross Abstract: Time series anomaly detection is a crucial task in various domains, including finance, healthcare, and industry. However, existing methods often struggle to generalize across different datasets, especially when anomalies are subtle or context-dependent. To solve this issue, we introduce ChronosAD, a novel architecture for anomaly detection that uses a time series