Add model card and metadata

README.md

@@ -0,0 +1,31 @@
+---
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Composition-RL-8B
+
+This repository contains the **Composition-RL-8B** model, developed as part of the research presented in the paper [Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Models](https://huggingface.co/papers/2602.12036).
+
+## Model Description
+Composition-RL is a data-efficient Reinforcement Learning with Verifiable Rewards (RLVR) approach designed to improve the reasoning capabilities of Large Language Models. It addresses the issue of "too-easy" prompts (pass-rate = 1) by automatically composing multiple verifiable problems into a single, harder verifiable prompt. This ensures the model continues to receive informative training signals throughout the RL process.
+
+- **Initial Model:** Qwen3-8b-Base
+- **Training Dataset:** [MATH-Composition-199K](https://huggingface.co/datasets/xx18/MATH-Composition-199K)
+- **Task:** Mathematical Reasoning
+- **Paper:** [arXiv:2602.12036](https://arxiv.org/abs/2602.12036)
+- **Code:** [GitHub - Composition-RL](https://github.com/XinXU-USTC/Composition-RL)
+
+## Performance
+As detailed in the paper, Composition-RL-8B consistently improves reasoning capability over RL trained on original, non-compositional datasets across various benchmarks.
+
+## Citation
+If you find this work helpful, please consider citing:
+```bibtex
+@article{xu2026composition-rl,
+  title={Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Models},
+  author={Xu, Xin and Bai, Clive and Yang, Kai and Chen, Tianhao and Chen, Yangkun and Liu, Weijie and Chen, Hao and Wang, Yang and Yang, Saiyong and Yang, Can},
+  journal={arXiv preprint arXiv:2602.12036},
+  year={2026}
+}
+```