{"total":28,"rows":[{"id":"2308.15366","title":"AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models","created":"2023-08-29","cited_by_count":171,"area":"mllm"},{"id":"2310.19070","title":"Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly Detection","created":"2023-10-29","cited_by_count":39,"area":"mllm"},{"id":"2404.09654","title":"Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection","created":"2024-04-15","cited_by_count":36,"area":"mllm"},{"id":"2407.21794","title":"Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey","created":"2024-07-31","cited_by_count":36,"area":"mllm"},{"id":"2311.02612","title":"GPT-4V-AD: Exploring Grounding Potential of VQA-oriented GPT-4V for Zero-shot Anomaly Detection","created":"2023-11-05","cited_by_count":23,"area":"mllm"},{"id":"2505.09265","title":"MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning","created":"2025-05-14","cited_by_count":13,"area":"mllm"},{"id":"2508.13560","title":"DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup","created":"2025-08-19","cited_by_count":10,"area":"mllm"},{"id":"2409.00556","title":"FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language Model","created":"2024-08-31","cited_by_count":7,"area":"mllm"},{"id":"2510.09867","title":"Cluster-Aware Prompt Ensemble Learning for Few-Shot Vision-Language Model Adaptation","created":"2025-10-10","cited_by_count":7,"area":"mllm"},{"id":"2505.02626","title":"Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models","created":"2025-05-05","cited_by_count":6,"area":"mllm"},{"id":"2507.07939","title":"SAGE: A Visual Language Model for Anomaly Detection via Fact Enhancement and Entropy-aware Alignment","created":"2025-07-10","cited_by_count":4,"area":"mllm"},{"id":"2605.20284","title":"JUDO: A Juxtaposed Domain-Oriented Multimodal Reasoner for Industrial Anomaly QA","created":"2026-05-19","cited_by_count":4,"area":"mllm"},{"id":"2511.08173","title":"VLMDiff: Leveraging Vision-Language Models for Multi-Class Anomaly Detection with Diffusion","created":"2025-11-11","cited_by_count":3,"area":"mllm"},{"id":"2407.03634","title":"SOWA: Adapting Hierarchical Frozen Window Self-Attention to Visual-Language Models for Better Anomaly Detection","created":"2024-07-04","cited_by_count":2,"area":"mllm"},{"id":"2510.16036","title":"IAD-GPT: Advancing Visual Knowledge in Multimodal Large Language Model for Industrial Anomaly Detection","created":"2025-10-16","cited_by_count":2,"area":"mllm"},{"id":"2605.20682","title":"IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools","created":"2026-05-20","cited_by_count":2,"area":"mllm"},{"id":"2403.09493","title":"Anomaly Detection by Adapting a pre-trained Vision Language Model","created":"2024-03-14","cited_by_count":1,"area":"mllm"},{"id":"2604.10971","title":"MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models","created":"2026-04-13","cited_by_count":1,"area":"mllm"},{"id":"2412.00890","title":"Exploring Large Vision-Language Models for Robust and Efficient Industrial Anomaly Detection","created":"2024-12-01","cited_by_count":0,"area":"mllm"},{"id":"2502.09057","title":"Vision-Language In-Context Learning Driven Few-Shot Visual Inspection Model","created":"2025-02-13","cited_by_count":0,"area":"mllm"},{"id":"2508.07819","title":"ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection","created":"2025-08-11","cited_by_count":0,"area":"mllm"},{"id":"2508.16157","title":"Beyond Human-prompting: Adaptive Prompt Tuning with Semantic Alignment for Anomaly Detection","created":"2025-08-22","cited_by_count":0,"area":"mllm"},{"id":"2512.09446","title":"Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation","created":"2025-12-10","cited_by_count":0,"area":"mllm"},{"id":"2603.21824","title":"SteelDefectX: A Multi-Form Vision-Language Dataset and Benchmark for Steel Surface Defect Analysis","created":"2026-03-23","cited_by_count":0,"area":"mllm"},{"id":"2605.05161","title":"Wasserstein-Aligned Localisation for VLM-Based Distributional OOD Detection in Medical Imaging","created":"2026-05-06","cited_by_count":0,"area":"mllm"},{"id":"2608.23723","title":"DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection","created":"2026-08-24","cited_by_count":0,"area":"mllm"},{"id":"2609.07229","title":"Proximity-CLIP: Text-Guided Semantic Proximity Learning for Zero-Shot Anomaly Detection","created":"2026-09-07","cited_by_count":0,"area":"mllm"},{"id":"2609.39033","title":"TED:Text-Axis Evidence Decomposition for Prompted Anomaly Localization","created":"2026-09-30","cited_by_count":0,"area":"mllm"}],"next_cursor":null}