2026
TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning
CVPR 2026
Enhancing temporal understanding of MLLMs is essential for long-form video analysis, supporting tasks such as temporal localization and time-sensitive question answering. While reinforcement learning (RL) has been explored for temporal reasoning, existing approaches are often limited to specific tas