SOURCE-LINKED INTELLIGENCE
VideoGen-Agent: Reinforcing Video Generation Agents
Recent advances in video generative models have enabled high-fidelity, temporally coherent video generation. However, these models often struggle to satisfy prompts requiring specialized knowledge, specific identities, physical consistency, or ordered events. In this paper, we present VideoGen-Agent, a multimodal agent trained through multitask agentic reinforcement learning to use external tools for video generation. The agent coordinates augmentation, generation, and verification tools through multi-turn interactions, using the prompt and intermediate observations to guide its decisions. We
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-21T17:58:56.000Z
First collected: 2026-09-23T06:11:12.848Z. This is not the publication date.