{"total":57,"rows":[{"id":"2403.06495","title":"Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Prompts","created":"2024-03-11","cited_by_count":89,"area":null},{"id":"2412.06171","title":"Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity","created":"2024-12-09","cited_by_count":70,"area":"mllm"},{"id":"2406.12235","title":"Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM","created":"2024-06-18","cited_by_count":64,"area":"mllm"},{"id":"2405.16886","title":"Hawk: Learning to Understand Open-World Video Anomalies","created":"2024-05-27","cited_by_count":49,"area":null},{"id":"2409.09957","title":"Deep Graph Anomaly Detection: A Survey and New Perspectives","created":"2024-09-16","cited_by_count":40,"area":null},{"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":"2409.05383","title":"Deep Learning for Video Anomaly Detection: A Review","created":"2024-09-09","cited_by_count":27,"area":null},{"id":"2412.01095","title":"VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models","created":"2024-12-02","cited_by_count":24,"area":"mllm"},{"id":"2505.23504","title":"VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-Tuning","created":"2025-05-29","cited_by_count":24,"area":null},{"id":"2410.10289","title":"Fine-grained Abnormality Prompt Learning for Zero-shot Anomaly Detection","created":"2024-10-14","cited_by_count":22,"area":null},{"id":"2505.12589","title":"SurveillanceVQA-589K: A Benchmark for Comprehensive Surveillance Video-Language Understanding with Large Models","created":"2025-05-19","cited_by_count":18,"area":null},{"id":"2503.18094","title":"Anomize: Better Open Vocabulary Video Anomaly Detection","created":"2025-03-23","cited_by_count":13,"area":null},{"id":"2505.15205","title":"Flashback: Memory-Driven Zero-shot, Real-time Video Anomaly Detection","created":"2025-05-21","cited_by_count":12,"area":null},{"id":"2511.00962","title":"A Unified Reasoning Framework for Holistic Zero-Shot Video Anomaly Analysis","created":"2025-11-02","cited_by_count":12,"area":null},{"id":"2411.14565","title":"Privacy-Preserving Video Anomaly Detection: A Survey","created":"2024-11-21","cited_by_count":11,"area":null},{"id":"2503.03562","title":"Towards Visual Discrimination and Reasoning of Real-World Physical Dynamics: Physics-Grounded Anomaly Detection","created":"2025-03-05","cited_by_count":10,"area":null},{"id":"2507.17394","title":"HiProbe-VAD: Video Anomaly Detection via Hidden States Probing in Tuning-Free Multimodal LLMs","created":"2025-07-23","cited_by_count":9,"area":null},{"id":"2411.10922","title":"Exploiting VLM Localizability and Semantics for Open Vocabulary Action Detection","created":"2024-11-17","cited_by_count":8,"area":null},{"id":"2503.13160","title":"Language-guided Open-world Video Anomaly Detection under Weak Supervision","created":"2025-03-17","cited_by_count":8,"area":null},{"id":"2510.02155","title":"Unlocking Vision-Language Models for Video Anomaly Detection via Fine-Grained Prompting","created":"2025-10-02","cited_by_count":8,"area":"mllm"},{"id":"2602.19248","title":"No Need For Real Anomaly: MLLM Empowered Zero-Shot Video Anomaly Detection","created":"2026-02-22","cited_by_count":8,"area":null},{"id":"2504.04495","title":"AVadCLIP: Audio-Visual Collaboration for Robust Video Anomaly Detection","created":"2025-04-06","cited_by_count":7,"area":null},{"id":"2412.03044","title":"Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection","created":"2024-12-04","cited_by_count":6,"area":"diffusion"},{"id":"2406.01170","title":"Zero-Shot Out-of-Distribution Detection with Outlier Label Exposure","created":"2024-06-03","cited_by_count":5,"area":null},{"id":"2507.21649","title":"The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM","created":"2025-07-29","cited_by_count":4,"area":null},{"id":"2510.14896","title":"Leveraging Multimodal LLM Descriptions of Activity for Explainable Semi-Supervised Video Anomaly Detection","created":"2025-10-16","cited_by_count":4,"area":"mllm"},{"id":"2601.08155","title":"Instance-Aligned Captions for Explainable Video Anomaly Detection","created":"2026-01-13","cited_by_count":4,"area":null},{"id":"2602.24021","title":"Steering and Rectifying Latent Representation Manifolds in Frozen Multi-modal LLMs for Video Anomaly Detection","created":"2026-02-27","cited_by_count":4,"area":"mllm"},{"id":"2505.19022","title":"Rethinking Metrics and Benchmarks of Video Anomaly Detection","created":"2025-05-25","cited_by_count":3,"area":null},{"id":"2506.13095","title":"Learning Event Completeness for Weakly Supervised Video Anomaly Detection","created":"2025-06-16","cited_by_count":3,"area":null},{"id":"2510.23190","title":"Evaluation of Vision-LLMs in Surveillance Video","created":"2025-10-27","cited_by_count":3,"area":null},{"id":"2603.00550","title":"Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning","created":"2026-02-28","cited_by_count":3,"area":null},{"id":"2403.01169","title":"Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection","created":"2024-03-02","cited_by_count":2,"area":null},{"id":"2511.00524","title":"Text-guided Fine-Grained Video Anomaly Understanding","created":"2025-11-01","cited_by_count":2,"area":null},{"id":"2605.08003","title":"SphereVAD: Training-Free Video Anomaly Detection via Geodesic Inference on the Unit Hypersphere","created":"2026-05-08","cited_by_count":2,"area":null},{"id":"2607.20780","title":"Rethinking Open-World Video Anomaly Detection: Diagnosing Definition Blindness","created":"2026-07-22","cited_by_count":2,"area":null},{"id":"2505.02393","title":"Uncertainty-Weighted Fusion of Image and Synthetic Event for Video Anomaly Detection","created":"2025-05-05","cited_by_count":1,"area":null},{"id":"2508.00312","title":"GV-VAD : Exploring Video Generation for Weakly-Supervised Video Anomaly Detection","created":"2025-08-01","cited_by_count":1,"area":null},{"id":"2601.02927","title":"PrismVAU: Prompt-Refined Inference System for Multimodal Video Anomaly Understanding","created":"2026-01-06","cited_by_count":1,"area":null},{"id":"2603.24991","title":"Towards Video Anomaly Detection from Event Streams: A Baseline and Benchmark Datasets","created":"2026-03-26","cited_by_count":1,"area":null},{"id":"2604.03040","title":"QVAD: A Question-Centric Agentic Framework for Efficient and Training-Free Video Anomaly Detection","created":"2026-04-03","cited_by_count":1,"area":"agents"},{"id":"2604.07772","title":"ESOM: Efficiently Understanding Streaming Video Anomalies with Open-world Dynamic Definitions","created":"2026-04-09","cited_by_count":1,"area":null},{"id":"2605.12725","title":"Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models","created":"2026-05-12","cited_by_count":1,"area":null},{"id":"2605.15325","title":"COPRA: Conditional Parameter Adaptation with Reinforcement Learning for Video Anomaly Detection","created":"2026-05-14","cited_by_count":1,"area":"lr"},{"id":"2609.17211","title":"Probe-VAD: Ordinal Likelihood Probing for Training-Free Video Anomaly Detection","created":"2026-09-15","cited_by_count":1,"area":null},{"id":"2504.18866","title":"PiercingEye: Dual-Space Video Violence Detection with Hyperbolic Vision-Language Guidance","created":"2025-04-26","cited_by_count":0,"area":null},{"id":"2510.20268","title":"GMFVAD: Using Grained Multi-modal Feature to Improve Video Anomaly Detection","created":"2025-10-23","cited_by_count":0,"area":null},{"id":"2512.06845","title":"PA-VAD: Diffusion-Based Pseudo-Only Video Anomaly Detection via Domain-Aligned Memory Updates","created":"2025-12-07","cited_by_count":0,"area":null},{"id":"2602.17077","title":"Cross Pseudo Labeling For Weakly Supervised Video Anomaly Detection","created":"2026-02-19","cited_by_count":0,"area":null},{"id":"2604.04632","title":"InCTRLv2: Generalist Residual Models for Few-Shot Anomaly Detection and Segmentation","created":"2026-04-06","cited_by_count":0,"area":null},{"id":"2605.24503","title":"FoodMonitor: Benchmarking MLLMs for Explainable Compliance Analysis","created":"2026-05-23","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":"2607.09114","title":"Event Stream based Multi-Modal Video Anomaly Detection: A Benchmark Dataset and Algorithms","created":"2026-07-10","cited_by_count":0,"area":null},{"id":"2608.06876","title":"FedVAR: Prototype-Aligned Federated Framework for Video Anomaly Recognition","created":"2026-08-07","cited_by_count":0,"area":null},{"id":"2608.21854","title":"Look Inside Each Video: Rethinking How Video Anomaly Detection Is Evaluated","created":"2026-08-22","cited_by_count":0,"area":null},{"id":"2609.17843","title":"RoboVAD: A Large Cross-Domain Evaluation Benchmark for Anomaly Detection in Robotic Arm Manipulation Videos","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.31753","title":"Beyond Isolated Entities: Relation-Aware Multi-Entity Modeling for Unsupervised Video Anomaly Detection","created":"2026-09-23","cited_by_count":0,"area":null}],"next_cursor":null}