A Hybrid Framework for Time Series Anomaly Detection with LLMs
Large Language Models (LLMs) are increasingly explored for time series anomaly detection (TSAD), yet their direct use often remains inferior to methods designed specifically for TSAD. In this work, we study whether this limitation arises primarily from weak forecasting or from insufficient exploitation of forecast resi...