2026
Incentivizing Versatile Video Reasoning in MLLMs via Data-Efficient Reinforcement Learning
CVPR 2026
Multimodal Large Language Models (MLLMs) have made great progress in video understanding tasks. However, when it comes to understanding complex or lengthy videos, MLLMs tend to overlook details or produce hallucinations. To alleviate these issues, recent work has attempted to leverage reinforcement