7 papers
VI-Bench: Benchmarking Prompt Inversion from AIGC Videos
Wulin Xie, Rui Zhao, Kecen Li +5
Recent advances in video generation have made prompt-based control increasingly central to AIGC video generation. Prompts specify what a video should depict and how it should be re…
DyCo-RL: Dynamic Cross-Modal Coordination for Visual Reasoning
Hangui Lin, Yan Shu, Zhengyang Liang +8
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a leading paradigm for enhancing visual reasoning in Multimodal Large Language Models (MLLMs). However, existin…
Video-Browser: Towards Open-web Agentic Video Browsing
Zhengyang Liang, Yan Shu, Xiangrui Liu +6
Autonomous agents are shifting information seeking from passive retrieval toward proactive, open-ended research, yet this progress has largely bypassed video, one of the web's rich…
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…
Video-XL-Pro: Reconstructive Token Compression for Extremely Long Video Understanding
Xiangrui Liu, Yan Shu, Zheng Liu +3
Despite advanced token compression techniques, existing multimodal large language models (MLLMs) still struggle with hour-long video understanding. In this work, we propose Video-X…
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…
MMCR: Benchmarking Cross-Source Reasoning in Scientific Papers
Yang Tian, Zheng Lu, Mingqi Gao +2
Fully comprehending scientific papers by machines reflects a high level of Artificial General Intelligence, requiring the ability to reason across fragmented and heterogeneous sour…