AI RESEARCH
IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools
arXiv CS.CV
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ArXi:2605.20682v1 Announce Type: new Multimodal large language models (MLLMs) have shown remarkable capability in bridging visual perception and textual reasoning, enabling zero-shot understanding across diverse industrial scenarios. However, their performance in open-vocabulary industrial anomaly detection (IAD) is often limited by domain-misaligned reasoning and hallucinated structural inferences. To address these challenges, we propose \textbf{IndusAgent}, a tool-augmented agentic framework for open-vocabulary