{"total":32,"rows":[{"id":"2409.05383","title":"Deep Learning for Video Anomaly Detection: A Review","created":"2024-09-09","cited_by_count":27,"area":null},{"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":"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":"2412.14056","title":"A Review of Multimodal Explainable Artificial Intelligence: Past, Present and Future","created":"2024-12-18","cited_by_count":9,"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":"2507.21507","title":"VAGU & GtS: LLM-Based Benchmark and Framework for Joint Video Anomaly Grounding and Understanding","created":"2025-07-29","cited_by_count":8,"area":null},{"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":"2408.14329","title":"Towards Adaptive Human-centric Video Anomaly Detection: A Comprehensive Framework and A New Benchmark","created":"2024-08-26","cited_by_count":6,"area":null},{"id":"2511.19474","title":"Pistachio: Towards Synthetic, Balanced, and Long-Form Video Anomaly Benchmarks","created":"2025-11-22","cited_by_count":5,"area":null},{"id":"2512.04532","title":"PhyVLLM: Physics-Guided Video Language Model with Motion-Appearance Disentanglement","created":"2025-12-04","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":"2511.00613","title":"CueBench: Advancing Unified Understanding of Context-Aware Video Anomalies in Real-World","created":"2025-11-01","cited_by_count":4,"area":null},{"id":"2511.07299","title":"VADER: Towards Causal Video Anomaly Understanding with Relation-Aware Large Language Models","created":"2025-11-10","cited_by_count":4,"area":null},{"id":"2601.08155","title":"Instance-Aligned Captions for Explainable Video Anomaly Detection","created":"2026-01-13","cited_by_count":4,"area":null},{"id":"2607.00622","title":"Learning to Watch: Active Video Anomaly Understanding via Interleaved Policy Optimization","created":"2026-07-01","cited_by_count":4,"area":null},{"id":"2601.17258","title":"FineVAU: A Novel Human-Aligned Benchmark for Fine-Grained Video Anomaly Understanding","created":"2026-01-24","cited_by_count":3,"area":null},{"id":"2511.00524","title":"Text-guided Fine-Grained Video Anomaly Understanding","created":"2025-11-01","cited_by_count":2,"area":null},{"id":"2605.07575","title":"Response-G1: Explicit Scene Graph Modeling for Proactive Streaming Video Understanding","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":"2608.03779","title":"AgenticVAU: Multi-Agent Explore-Verify Reasoning for Video Anomaly Understanding","created":"2026-08-04","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":"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":"2604.07772","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":"2608.05699","title":"TAU-Bench: From Anomaly Instance Tracking to Fine-Grained Video Anomaly Understanding","created":"2026-08-06","cited_by_count":1,"area":null},{"id":"2608.06913","title":"MuST-VAD: Mutual Structured Learning for Video Anomaly Detection","created":"2026-08-07","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":"2610.02019","title":"Controllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.16299","title":"Learning Temporal Evidence Selection for Video Anomaly Understanding","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.16324","title":"Anomaly-Guided Observation and Two-Level Semantic Feedback for Training-Free Video Anomaly Analysis","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}