Reinforcement learning trains video AI agents to use external tools effectively

VideoGen-Agent coordinates augmentation, generation and verification tools through multi-turn interactions, boosting benchmark scores by 19 points without retraining the underlying video model.

Top University
Binxu Li · Haoyi Duan · Yuhui Zhang · Yaohui Zhang · Zihao Lin · Kaituo Feng · +6 more

Princeton University · Stanford University · UC Davis · MMLab, CUHK · Independent

Research Digest··3 min read
The authors present VideoGen-Agent, a multimodal agent trained via multitask agentic reinforcement learning to orchestrate external tools for video generation.

The authors developed VideoGen-Agent, a multimodal agent that combines a large language model with vision capabilities to use external tools for video generation.

Why this paper

From Princeton University and 6 others

In one line

A multimodal agent trained via multitask reinforcement learning coordinates external tools to improve video generation quality and accuracy.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ·No benchmark numbers found

Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.

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