Author

Xingdong Sheng

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Preprint Aug 2026

Test-time Reinforcement Learning for Anomalous Video Understanding

Anomalous video understanding aims to identify abnormal events in videos and interpret their semantic meanings beyond simple anomaly detection. Recent video large language models (Video-LLMs) have demonstrated promising zero-shot capabilities for this task, yet their performance remains limited due to insufficient adap...

Hui-Ning Li, Yu-Xiang Duan, Ji-Yang Tan et al. · 0 citations

Preprint Aug 2026

AgenticVAU: Multi-Agent Explore-Verify Reasoning for Video Anomaly Understanding

AgenticVAU is presented, a training-free multi-agent framework that casts VAU as an explore--verify process, where the system first discovers potential anomalies and then verifies them through targeted observations until sufficient evidence is collected.

Yu-Xiang Duan, Hui-Ning Li, Aonian Li et al. · 2 citations