activity
20242026
collaborators

9 papers

cs.CV2026

One Skill Does Not Fit All: Automatic Discovery and Taxonomy-Guided Routing of Frame-Selection Skills for Long-Video Question Answering

Jian Hu, Zixu Cheng, Da Li +3

Long-Video Question Answering (LVQA) requires locating decisive evidence in hour-scale videos under a limited frame budget. Most training-free methods apply the same frame-selectio…

cs.CV2026

Each Judge Its Own Yardstick: Discovering Per-VLM Taxonomies for Physical Video Evaluation

Yu Cao, Ziquan Liu, Zhensong Zhang +3

Maintaining physical consistency in video generators and world models increasingly relies on vision-language models (VLMs) as automated judges that provide reward signals, ranking…

cs.CV2026

LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution

Yu Cao, Ziquan Liu, Zhensong Zhang +3

Adapting large-scale pre-trained video generators for Video Super-Resolution (VSR) in novel domains remains computationally prohibitive. Methods that reformulate generation as dire…

cs.CV2026

Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation

Zengqun Zhao, Yanzuo Lu, Ziquan Liu +3

Autoregressive video diffusion has recently emerged as a promising paradigm for long-video generation, enabling causal synthesis beyond the temporal limits of bidirectional models.…

cs.CV2026

LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion

Zengqun Zhao, Ziquan Liu, Yu Cao +5

The recent success of inference-time scaling in large language models has inspired similar explorations in video diffusion. In particular, motivated by the existence of "golden noi…

cs.CV2026

GraphThinker: Reinforcing Temporally Grounded Video Reasoning with Event Graph Thinking

Zixu Cheng, Da Li, Jian Hu +4

Video reasoning requires a fine-grained understanding of the temporal dependencies and event-level relations between objects and events in videos. Current Multimodal Large Language…