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VideoGen-Agent: Reinforcing Video Generation Agents

This paper introduces VideoGen-Agent, a multimodal agent trained using multitask agentic reinforcement learning to generate videos by utilizing external tools. The agent uses a shared policy trained on a balanced dataset and a hybrid reward system to evaluate tool use and video quality. On a benchmark called VABench, VideoGen-Agent outperforms its base text-to-video generator by 19.1 points, achieving a score of 75.6, and further improvements are possible with better generation tools.

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PublishedSeptember 21, 2026Binxu Li, Haoyi Duan, Yuhui Zhang
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WHY IT MAY MATTER

This approach improves video generation by using an agent that coordinates tools through reinforcement learning, leading to better performance on specific tasks and allowing future tool advancements to further enhance results.

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