collaborators

7 papers

cs.CV2026

Memento: Reconstruct to Remember for Consistent Long Video Generation

Xuan Wei, Longbin Ji, Guan Wang +5

Long-form video generation requires recurring subjects to remain consistent across various shots, viewpoints, motions, and scene transitions. Existing temporal decomposition method…

cs.CV2026

DyCo-RL: Dynamic Cross-Modal Coordination for Visual Reasoning

Hangui Lin, Yan Shu, Zhengyang Liang +6

Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a leading paradigm for enhancing visual reasoning in Multimodal Large Language Models (MLLMs). However, existin…

cs.CV2026

Video-Browser: Towards Agentic Open-web Video Browsing

Zhengyang Liang, Yan Shu, Xiangrui Liu +5

The evolution of autonomous agents is redefining information seeking, transitioning from passive retrieval to proactive, open-ended web research. However, a significant modality ga…

cs.CV2025

TimeScope: Towards Task-Oriented Temporal Grounding In Long Videos

Xiangrui Liu, Minghao Qin, Yan Shu +5

Identifying key temporal intervals within long videos, known as temporal grounding (TG), is important to video understanding and reasoning tasks. In this paper, we introduce a new…

cs.CV2025

STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?

Yun Li, Yiming Zhang, Tao Lin +4

The use of Multimodal Large Language Models (MLLMs) as an end-to-end solution for Embodied AI and Autonomous Driving has become a prevailing trend. While MLLMs have been extensivel…

cs.CV2025

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification

Minghao Qin, Xiangrui Liu, Zhengyang Liang +6

Multi-modal large language models (MLLMs) models have made significant progress in video understanding over the past few years. However, processing long video inputs remains a majo…