2 papers
cs.CV2026
RewardVerse: Rubric-Guided Policy Optimization for Video Reward Modeling
Zhenchen Tang, Yang Li, Songlin Yang +6
Reinforcement learning (RL) is vital for optimizing video generation models, with a robust reward model (RM) serving as the cornerstone. However, existing video reward models often…
cs.CV2026
OmniVBench: A Benchmark and Large-Scale Dataset for Omni Reference-to-Video Generation
Wenxue Li, Peiyan Guan, Haoyang Jiang +14
Reference-to-video (R2V) generation is evolving toward increasingly general and versatile reference control, giving rise to the emerging paradigm of omni R2V generation. However, e…