4 papers
FinMTM: A Multi-Turn Multimodal Benchmark for Financial Reasoning and Agent Evaluation
Chenxi Zhang, Ziliang Gan, Liyun Zhu +3
The financial domain poses substantial challenges for vision-language models (VLMs) due to specialized chart formats and knowledge-intensive reasoning requirements. However, existi…
VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-Tuning
Liyun Zhu, Qixiang Chen, Xi Shen +1
Video Anomaly Understanding (VAU) is essential for applications such as smart cities, security surveillance, and disaster alert systems, yet remains challenging due to its demand f…
Learnable Expansion of Graph Operators for Multi-Modal Feature Fusion
Dexuan Ding, Lei Wang, Liyun Zhu +2
In computer vision tasks, features often come from diverse representations, domains (e.g., indoor and outdoor), and modalities (e.g., text, images, and videos). Effectively fusing…
Advancing Video Anomaly Detection: A Concise Review and a New Dataset
Liyun Zhu, Lei Wang, Arjun Raj +2
Video Anomaly Detection (VAD) finds widespread applications in security surveillance, traffic monitoring, industrial monitoring, and healthcare. Despite extensive research efforts,…