Cover Image

AnomalyAgent: Agentic Industrial Anomaly Synthesis via Tool-Augmented Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Su, Jiaming, Yang, Tengchao, Zhang, Ruikang, Yan, Zhengan, Sun, Haoyu, Zhang, Linfeng
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection
by: Zhang, Yi, et al.
Published: (2026)

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools
by: Tan, Rongbin, et al.
Published: (2026)

AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation
by: Miao, Junwen, et al.
Published: (2025)

ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining
by: Yao, Xincheng, et al.
Published: (2025)

Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection
by: Chen, Qiyu, et al.
Published: (2024)

Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection
by: Chen, Qiyu, et al.
Published: (2025)

A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
by: Chen, Qiyu, et al.
Published: (2024)

CXR-AD: Component X-ray Image Dataset for Industrial Anomaly Detection
by: Bai, Haoyu, et al.
Published: (2025)

Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection
by: Tong, Xuan, et al.
Published: (2025)

Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection
by: Chen, Xin, et al.
Published: (2024)

AnomalyClaw: A Universal Visual Anomaly Detection Agent via Tool-Grounded Refutation
by: Jiang, Xi, et al.
Published: (2026)

Referring Industrial Anomaly Segmentation
by: Yue, Pengfei, et al.
Published: (2026)

Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection
by: Lu, Yilin, et al.
Published: (2025)

ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
by: Zhang, Qunyi, et al.
Published: (2025)

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment
by: Xu, Xichen, et al.
Published: (2025)

IPAD: Industrial Process Anomaly Detection Dataset
by: Liu, Jinfan, et al.
Published: (2024)

Patho-AgenticRAG: Towards Multimodal Agentic Retrieval-Augmented Generation for Pathology VLMs via Reinforcement Learning
by: Zhang, Wenchuan, et al.
Published: (2025)

AnomalyPainter: Vision-Language-Diffusion Synergy for Zero-Shot Realistic and Diverse Industrial Anomaly Synthesis
by: Lai, Zhangyu, et al.
Published: (2025)

Cross-Modal Learning for Anomaly Detection in Complex Industrial Process: Methodology and Benchmark
by: Wu, Gaochang, et al.
Published: (2024)

Noise Fusion-based Distillation Learning for Anomaly Detection in Complex Industrial Environments
by: Yu, Jiawen, et al.
Published: (2025)

Towards High-Resolution Industrial Image Anomaly Detection
by: Zhang, Ximiao, et al.
Published: (2025)

RAID: Retrieval-Augmented Anomaly Detection
by: Cai, Mingxiu, et al.
Published: (2026)

A Survey on Industrial Anomalies Synthesis
by: Wang, Yanshu, et al.
Published: (2025)

ToCoAD: Two-Stage Contrastive Learning for Industrial Anomaly Detection
by: Liang, Yun, et al.
Published: (2024)

ProtoAnomalyNCD: Prototype Learning for Multi-class Novel Anomaly Discovery in Industrial Scenarios
by: Zhao, Botong, et al.
Published: (2025)

Multimodal Industrial Anomaly Detection via Geometric Prior
by: Li, Min, et al.
Published: (2026)

AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios
by: Huang, Ziming, et al.
Published: (2024)

Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift
by: Liao, Jingyi, et al.
Published: (2025)

On the Problem of Consistent Anomalies in Zero-Shot Industrial Anomaly Detection
by: Le-Gia, Tai, et al.
Published: (2025)

PANDA: Towards Generalist Video Anomaly Detection via Agentic AI Engineer
by: Yang, Zhiwei, et al.
Published: (2025)

Robust Anomaly Detection in Industrial Environments via Meta-Learning
by: Aqeel, Muhammad, et al.
Published: (2025)

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis
by: Liu, Yishen, et al.
Published: (2026)

AF-CLIP: Zero-Shot Anomaly Detection via Anomaly-Focused CLIP Adaptation
by: Fang, Qingqing, et al.
Published: (2025)

AnomalyXFusion: Multi-modal Anomaly Synthesis with Diffusion
by: Hu, Jie, et al.
Published: (2024)

MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection
by: Hu, Jinwei, et al.
Published: (2026)

IAD-Unify: A Region-Grounded Unified Model for Industrial Anomaly Segmentation, Understanding, and Generation
by: Zheng, Haoyu, et al.
Published: (2026)

RcAE: Recursive Reconstruction Framework for Unsupervised Industrial Anomaly Detection
by: Wu, Rongcheng, et al.
Published: (2025)

ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning
by: Yang, Zuhao, et al.
Published: (2026)

Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning
by: Chen, Peng, et al.
Published: (2026)

Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection
by: Tu, Yuanpeng, et al.
Published: (2024)