Improve model card: add metadata and project links

README.md

@@ -1,17 +1,36 @@
 ---
 license: apache-2.0
+library_name: transformers
+pipeline_tag: video-text-to-text
+tags:
+- multimodal
+- agent
+- reinforcement-learning
 ---
 
-[PyVision-RL: Forging Open Agentic Vision Models via RL](https://arxiv.org/abs/2602.20739)
+# PyVision-Video-7B-RL
 
-This is PyVision-Video-7B-RL, post trained from Qwen2.5-VL-7B.
+[**PyVision-RL: Forging Open Agentic Vision Models via RL**](https://huggingface.co/papers/2602.20739)
+
+PyVision-Video-7B-RL is an open-weight agentic multimodal model post-trained from [Qwen2.5-VL-7B](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) using reinforcement learning.
+
+- **Project Page:** [agent-x.space/pyvision-rl](https://agent-x.space/pyvision-rl/)
+- **GitHub Repository:** [agents-x-project/PyVision-RL](https://github.com/agents-x-project/PyVision-RL)
+- **Paper:** [arXiv:2602.20739](https://arxiv.org/abs/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{pyvisionrl2026,
-  title={PyVision-RL: Forging Open Agentic Vision Models via RL},
+@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:2602.20739},
-  year={2026}
+  journal={arxiv preprint arxiv:2602.20739},
+  year={2026},
 }
-```
-
+```