{"total":22,"rows":[{"id":"2510.26464","title":"Towards Fine-Grained Vision-Language Alignment for Few-Shot Anomaly Detection","created":"2025-10-30","cited_by_count":4,"area":null},{"id":"2601.05552","title":"One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection","created":"2026-01-09","cited_by_count":4,"area":null},{"id":"2507.13378","title":"A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects","created":"2025-07-15","cited_by_count":2,"area":null},{"id":"2509.17615","title":"From Benchmarks to Reality: Advancing Visual Anomaly Detection by the VAND 3.0 Challenge","created":"2025-09-22","cited_by_count":2,"area":null},{"id":"2511.20169","title":"ADNet: A Large-Scale and Extensible Multi-Domain Benchmark for Anomaly Detection Across 380 Real-World Categories","created":"2025-11-25","cited_by_count":2,"area":null},{"id":"2601.22763","title":"Is Task-Specific Training Necessary for Anomaly Detection?","created":"2026-01-30","cited_by_count":2,"area":null},{"id":"2504.11895","title":"Search is All You Need for Few-shot Anomaly Detection","created":"2025-04-16","cited_by_count":1,"area":null},{"id":"2508.11826","title":"From Pixels to Graphs: Deep Graph-Level Anomaly Detection on Dermoscopic Images","created":"2025-08-15","cited_by_count":1,"area":null},{"id":"2505.16659","title":"SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images","created":"2025-05-22","cited_by_count":0,"area":null},{"id":"2508.21795","title":"TMUAD: Enhancing Logical Capabilities in Unified Anomaly Detection Models with a Text Memory Bank","created":"2025-08-29","cited_by_count":0,"area":null},{"id":"2510.13643","title":"Adversarially Robust Few-Shot Anomaly Detection with Vision Foundation Models","created":"2025-10-15","cited_by_count":0,"area":null},{"id":"2601.03011","title":"ReCCur: A Recursive Corner-Case Curation Framework for Robust Vision-Language Understanding in Open and Edge Scenarios","created":"2026-01-06","cited_by_count":0,"area":null},{"id":"2603.13964","title":"VID-AD: A Dataset for Image-Level Logical Anomaly Detection under Vision-Induced Distraction","created":"2026-03-14","cited_by_count":0,"area":null},{"id":"2603.15300","title":"GATE-AD: Graph Attention Network Encoding For Few-Shot Industrial Visual Anomaly Detection","created":"2026-03-16","cited_by_count":0,"area":null},{"id":"2605.09089","title":"Field-Localized Forgery Detection for Digital Identity Documents","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2606.14475","title":"Value-order Decomposition for Generalist Anomaly Detection","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2606.22556","title":"HiMatch-AD: DINOv3-driven Hierarchical Matching for Training-free Medical Anomaly Detection","created":"2026-06-21","cited_by_count":0,"area":null},{"id":"2606.25915","title":"FunPiQ: A New Benchmark for Pixel-Level Quality Assessment in Fundus Images","created":"2026-06-24","cited_by_count":0,"area":null},{"id":"2606.29714","title":"UniVAD v2: Unified Visual Anomaly Detection via Support-Conditioned Boundary Construction","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2607.23924","title":"DuoAD: Leveraging [CLS] Dual Characteristics for Training-Free Few-Shot Anomaly Detection","created":"2026-07-27","cited_by_count":0,"area":null},{"id":"2608.04210","title":"PADFormer: Pose-agnostic Anomaly Detection from Sparse View Images","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2608.25168","title":"See More, Detect Less? Taming Information Leakage in Multi-View Anomaly Detection","created":"2026-08-25","cited_by_count":0,"area":null}],"next_cursor":null}