Time-RA reformulates time series anomaly detection as a reasoning-intensive generative task and provides the RATs40K multimodal benchmark to evaluate and improve LLM-based diagnosis.
Exathlon: A benchmark for explainable anomaly detection over time series
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Extending Matrix Profile to multidimensional time series yields the only method among 19 baselines that maintains high anomaly detection performance across unsupervised, supervised, and semi-supervised regimes on 119 datasets.
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Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback
Time-RA reformulates time series anomaly detection as a reasoning-intensive generative task and provides the RATs40K multimodal benchmark to evaluate and improve LLM-based diagnosis.
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Matrix Profile for Anomaly Detection on Multidimensional Time Series
Extending Matrix Profile to multidimensional time series yields the only method among 19 baselines that maintains high anomaly detection performance across unsupervised, supervised, and semi-supervised regimes on 119 datasets.
- Conditional Attribution for Root Cause Analysis in Time-Series Anomaly Detection