license: apache-2.0
library_name: transformers
pipeline_tag: video-text-to-text
tags:
- multimodal
- agent
- reinforcement-learning
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
@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},
}