A GRPO-based post-training recipe for video LLMs using discrete QA rewards plus continuous temporal IoU rewards with variance-based data selection outperforms SFT and Video-R1.
Vtg-llm: Integrating timestamp knowledge into video llms for enhanced video temporal grounding
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Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency
A GRPO-based post-training recipe for video LLMs using discrete QA rewards plus continuous temporal IoU rewards with variance-based data selection outperforms SFT and Video-R1.