Industrial Anomaly Detection via Defect-Grounded Reasoning in Visual Latent Space

arXiv:2609.29457 · cs.CV · Submitted 2026-09-24 · Read on arXiv

cs.CV

Submitted: 2026-09-24

Updated: 2026-09-24

Code: https://github.com/Yen666/Anomaly-LR

Terminology

• Latent Reasoning — 15× in this paper · explained in 2 episodes
• Trace — 9× in this paper · explained in 2 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Latent Space — 8× in this paper · explained in 7 episodes
• Latent Visual Reasoning — 8× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• GRPO — 2× in this paper · explained in 6 episodes
• Reasoning Traces — 2× in this paper · explained in 3 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Memory Augmentation — 1× in this paper · explained in 2 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes

Sources

• GPT-4o System Card
• Qwen2.5-VL Technical Report
• AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation
• Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning
• AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection
• OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning
• EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO
• AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparison

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