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Agents-X/PyVision-Video-7B-RL

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PyVision-Video-7B-RL

**PyVision-RL: Forging Open Agentic Vision Models via RL**

PyVision-Video-7B-RL is an open-weight agentic multimodal model post-trained from Qwen2.5-VL-7B using reinforcement learning.

—Project Page: agent-x.space/pyvision-rl
—GitHub Repository: agents-x-project/PyVision-RL
—Paper: arXiv:2602.20739

Overview

Reinforcement learning for agentic multimodal models often suffers from interaction collapse, where models learn to reduce tool usage and multi-turn reasoning. PyVision-RL is a framework designed to stabilize training and sustain interaction by combining an oversampling-filtering-ranking rollout strategy with an accumulative tool reward.

PyVision-Video specifically addresses the challenge of video reasoning using on-demand context construction. It selectively samples task-relevant frames during the reasoning process to significantly reduce visual token usage while maintaining high performance on complex multimodal agentic tasks.

Citation

bibtex

@article{zhao2026pyvisionrl,
  title={PyVision-RL: Forging Open Agentic Vision Models via RL.},
  author={Zhao, Shitian and Lin, Shaoheng and Li, Ming and Zhang, Haoquan and Peng, Wenshuo and Zhang, Kaipeng and Wei, Chen},
  journal={arxiv preprint arxiv:2602.20739},
  year={2026},
}