Author

H. Kang

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#artificial intelligence May 2026

Detecting Time Series Anomalies Like an Expert: A Multi-Agent LLM Framework with Specialized Analyzers

This work introduces SAGE (Specialized Analyzer Group for Expert-like Detection), a multi-agent framework for evidence-grounded diagnosis of univariate time series, which achieves an average Point-F1 of 66.26, the highest among the evaluated methods.

H. Kang, Jeongseob Kim, Jinwoo Park et al. · arXiv.org · 1 citation · ⚡1

#machine learning Preprint Sep 2026

Not All Variables Agree: Reliability-Aware Variable-Wise Gradient Surgery for Multivariate Time-Series Forecasting

Per-Variable Surgery (PV-Surgery) is proposed, an optimizer-side training strategy for backbones with cache-compatible layers that lowers MSE and MAE and indicates that the variable-wise structure hidden by mean-loss training is a usable optimization signal.

Jinwoo Park, H. Kang, Pilsung Kang · 0 citations