Cover Image

AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Junru, Feng, Lang, Shi, Haoran, Guo, Xu, Yu, Han, Dong, Yabo, Xu, Duanqing
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learning
by: Zhang, Junru, et al.
Published: (2025)

PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation
by: Zhang, Junru, et al.
Published: (2026)

Diverse Intra- and Inter-Domain Activity Style Fusion for Cross-Person Generalization in Activity Recognition
by: Zhang, Junru, et al.
Published: (2024)

ASTRO: Adaptive Spatio-Temporal Reinforcement Optimization for GNN Powered Anomly Detection in Cyber Physical Systems
by: Yar, Rai Ali, et al.
Published: (2026)

SeerAttention-R: Sparse Attention Adaptation for Long Reasoning
by: Gao, Yizhao, et al.
Published: (2025)

CircuitSeer: Mining High-Quality Data by Probing Mathematical Reasoning Circuits in LLMs
by: Wang, Shaobo, et al.
Published: (2025)

Tiny but Trusted: Efficient Vision-Language Reasoning for Time-Series Anomaly Detection
by: Zhou, Xiaona, et al.
Published: (2026)

Can LLMs Serve As Time Series Anomaly Detectors?
by: Dong, Manqing, et al.
Published: (2024)

ChatAD: Reasoning-Enhanced Time-Series Anomaly Detection with Multi-Turn Instruction Evolution
by: Sun, Hui, et al.
Published: (2026)

DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly Detection
by: Zhang, Wenxin, et al.
Published: (2025)

Angel or Devil: Discriminating Hard Samples and Anomaly Contaminations for Unsupervised Time Series Anomaly Detection
by: Zhang, Ruyi, et al.
Published: (2024)

A Graph-based Framework for Online Time Series Anomaly Detection Using Model Ensemble
by: Yu, Zewei, et al.
Published: (2026)

DARTs: A Dual-Path Robust Framework for Anomaly Detection in High-Dimensional Multivariate Time Series
by: Liu, Xuechun, et al.
Published: (2025)

ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning
by: Xie, Zhe, et al.
Published: (2024)

Formula-R1: Incentivizing LLM Reasoning over Complex Tables with Numerical Computation via Formula-Driven Reinforcement Learning
by: Cao, Lang, et al.
Published: (2025)

DRTA: Dynamic Reward Scaling for Reinforcement Learning in Time Series Anomaly Detection
by: Golchin, Bahareh, et al.
Published: (2025)

Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection
by: Xu, Hongzuo, et al.
Published: (2022)

IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection
by: Zhou, Xiaohui, et al.
Published: (2026)

Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series
by: Rahman, Maxx Richard, et al.
Published: (2024)

Warped Time Series Anomaly Detection
by: Lacoquelle, Charlotte, et al.
Published: (2024)

Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection
by: Chen, Katrina, et al.
Published: (2023)

Leveraging Intermediate Representations of Time Series Foundation Models for Anomaly Detection
by: Han, Chan Sik, et al.
Published: (2025)

SimAD: A Simple Dissimilarity-based Approach for Time Series Anomaly Detection
by: Zhong, Zhijie, et al.
Published: (2024)

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
by: Zhou, Yitong, et al.
Published: (2025)

Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection
by: Chen, Yutong, et al.
Published: (2024)

CCE: Confidence-Consistency Evaluation for Time Series Anomaly Detection
by: Zhong, Zhijie, et al.
Published: (2025)

Causal Disentanglement Learning for Accurate Anomaly Detection in Multivariate Time Series
by: Kim, Wonah, et al.
Published: (2025)

M$^3$Searcher: Modular Multimodal Information Seeking Agency with Retrieval-Oriented Reasoning
by: Yu, Xiaohan, et al.
Published: (2026)

Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection
by: Chen, Junqi, et al.
Published: (2024)

Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
by: Cho, Dongchan, et al.
Published: (2025)

Can Multimodal LLMs Perform Time Series Anomaly Detection?
by: Xu, Xiongxiao, et al.
Published: (2025)

Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
by: Chen, Junru, et al.
Published: (2024)

Clustering-based Anomaly Detection in Multivariate Time Series Data
by: Li, Jinbo, et al.
Published: (2025)

Faithful-First Reasoning, Planning, and Acting for Multimodal LLMs
by: Li, Junxian, et al.
Published: (2025)

SuperRL: Reinforcement Learning with Supervision to Boost Language Model Reasoning
by: Liu, Yihao, et al.
Published: (2025)

F-SE-LSTM: A Time Series Anomaly Detection Method with Frequency Domain Information
by: Lu, Yi-Xiang, et al.
Published: (2024)

FeynmanBench: Benchmarking Multimodal LLMs on Diagrammatic Physics Reasoning
by: Wang, Zeyu, et al.
Published: (2026)

IAD-R1: Reinforcing Consistent Reasoning in Industrial Anomaly Detection
by: Li, Yanhui, et al.
Published: (2025)

Small but Mighty: Enhancing Time Series Forecasting with Lightweight LLMs
by: Fan, Haoran, et al.
Published: (2025)

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework
by: Ghanim, Jihan, et al.
Published: (2024)