{"total":19,"rows":[{"id":"2409.01980","title":"Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey","created":"2024-09-03","cited_by_count":27,"area":null},{"id":"2411.02465","title":"See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers","created":"2024-11-04","cited_by_count":20,"area":null},{"id":"2507.12472","title":"A Survey of AIOps in the Era of Large Language Models","created":"2025-06-23","cited_by_count":19,"area":null},{"id":"2601.23204","title":"TSAQA: Time Series Analysis Question And Answering Benchmark","created":"2026-01-30","cited_by_count":11,"area":null},{"id":"2502.06911","title":"Foundation Models for Anomaly Detection: Vision and Challenges","created":"2025-02-10","cited_by_count":3,"area":null},{"id":"2506.11040","title":"Large Language models for Time Series Analysis: Techniques, Applications, and Challenges","created":"2025-05-21","cited_by_count":3,"area":null},{"id":"2503.21833","title":"Refining Time Series Anomaly Detectors using Large Language Models","created":"2025-03-26","cited_by_count":2,"area":null},{"id":"2508.19563","title":"Robustness is Important: Limitations of LLMs for Data Fitting","created":"2025-08-27","cited_by_count":2,"area":null},{"id":"2501.05675","title":"Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection","created":"2025-01-10","cited_by_count":1,"area":null},{"id":"2508.00047","title":"TriP-LLM: A Tri-Branch Patch-wise Large Language Model Framework for Time-Series Anomaly Detection","created":"2025-07-31","cited_by_count":1,"area":null},{"id":"2510.03962","title":"SPEAR: Soft Prompt Enhanced Anomaly Recognition for Time Series Data","created":"2025-10-04","cited_by_count":1,"area":null},{"id":"2505.15835","title":"Transforming Decoder-Only Transformers for Accurate WiFi-Telemetry Based Indoor Localization","created":"2025-05-16","cited_by_count":0,"area":null},{"id":"2509.18123","title":"SPADE: A Large Language Model Framework for Soil Moisture Pattern Recognition and Anomaly Detection in Precision Agriculture","created":"2025-09-10","cited_by_count":0,"area":null},{"id":"2510.04710","title":"ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts","created":"2025-10-06","cited_by_count":0,"area":null},{"id":"2510.17146","title":"Physics-Informed Large Language Models for HVAC Anomaly Detection with Autonomous Rule Generation","created":"2025-10-20","cited_by_count":0,"area":null},{"id":"2606.01691","title":"IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2607.25340","title":"Cardiologent: Multi-Agent Clinical Decision Support for Patient-Level Arrhythmia Assessment, Urgency, and Management","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2608.24113","title":"Structured Frequency-Domain Evidence for LLM-Based Time-Series Anomaly Detection","created":"2026-08-25","cited_by_count":0,"area":null},{"id":"2609.32123","title":"READ-Bench: Benchmarking Historical Instance Retrieval for Time-Series Diagnosis","created":"2026-09-26","cited_by_count":0,"area":null}],"next_cursor":null}