4 papers
LDDR: Linear-DPP-Based Dynamic-Resolution Frame Sampling for Video MLLMs
Jingfeng Chen, Jiawen Qian, Wendi Deng +5
Video understanding in multimodal large language models requires selecting informative frames from long, redundant videos under limited visual-token budgets. Existing methods often…
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
V Team, Wenyi Hong, Xiaotao Gu +94
We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…
VideoMiner: Iteratively Grounding Key Frames of Hour-Long Videos via Tree-based Group Relative Policy Optimization
Xinye Cao, Hongcan Guo, Jiawen Qian +6
Understanding hour-long videos with multi-modal large language models (MM-LLMs) enriches the landscape of human-centered AI applications. However, for end-to-end video understandin…
Exploring What Why and How: A Multifaceted Benchmark for Causation Understanding of Video Anomaly
Hang Du, Guoshun Nan, Jiawen Qian +7
Recent advancements in video anomaly understanding (VAU) have opened the door to groundbreaking applications in various fields, such as traffic monitoring and industrial automation…