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

arXiv:2605.05725 · cs.AI · Submitted 2026-05-07 · Read on arXiv

cs.AI

Submitted: 2026-05-07

Updated: 2026-09-25

Terminology

• Analyzer — 84× in this paper · explained in 1 episode
• Benchmark — 20× in this paper · explained in 2 episodes
• Ablation — 10× in this paper · explained in 1 episode
• Accuracy — 8× in this paper · explained in 1 episode
• Aggregation — 8× in this paper · explained in 1 episode
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Calibration — 3× in this paper · explained in 7 episodes
• Clustering — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Dynamic Time Warping — 2× in this paper
• F1 Score — 2× in this paper · explained in 3 episodes
• In-Context Learning — 2× in this paper · explained in 4 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Multi-Agent Framework — 2× in this paper · explained in 3 episodes
• Pairwise Comparisons — 2× in this paper · explained in 2 episodes
• Pruning — 2× in this paper · explained in 4 episodes
• Specialized Analyzer Group for Expert-like Detection — 2× in this paper
• Trace — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Dynamic Time Warping (DTW) — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In-Context Learning (ICL) — 1× in this paper · explained in 5 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Multi-agent Collaborative Framework — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• Wavelet Transform — 1× in this paper · explained in 2 episodes

Sources

• Large language models can be zero-shot anomaly detectors for time series?
• Can LLMs Serve As Time Series Anomaly Detectors?
• Constructing Large-Scale Real-World Benchmark Datasets for AIOps
• LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection
• MALT: Improving Reasoning with Multi-Agent LLM Training
• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
• See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers

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