Update README.md

Author: RyanLiu112

README.md

@@ -7,13 +7,50 @@
 </div>
 
 
+
 ## 🔔 News
 
 - **[2025-10-10]** ✨ Code is now available.
 - **[2025-09-30]** 📄 Our paper is released on [arXiv](https://arxiv.org/abs/2509.26628).
 
 
-## TBD
+
+## 🚀 Getting Started
+
+### Installation
+
+Clone the repository:
+
+```bash
+git clone https://github.com/RyanLiu112/AttnRL.git
+cd AttnRL
+```
+
+Create a new conda environment and install the dependencies:
+
+```bash
+conda create -n attnrl python=3.10
+conda activate attnrl
+bash scripts/install_vllm_sglang_mcore.sh
+```
+
+### Data Preparation
+
+The training dataset ([DeepScaleR-Preview-Dataset](https://huggingface.co/datasets/agentica-org/DeepScaleR-Preview-Dataset)) is at `data/train/deepscaler_train.parquet`, which contains `40.3k` mathematical reasoning data.
+The evaluation datasets are in `data/eval/` and the suffix `_${K}` indicates the number of duplicate samples for each question.
+
+### Training
+
+For training AttnRL with [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) backbone on 8 H100 GPUs, run:
+
+```bash
+bash recipe/attnrl/run_attnrl_r1_distill_1.5b_8k.sh
+```
+
+### Evaluation
+
+Evaluation scripts are the same as the training scripts. `+trainer.val_only=True` should be added to perform evaluation only. We recommend setting `data.max_prompt_length=2048` and `data.max_response_length=32768`.
+
 
 
 ## 📝 Citation
@@ -23,7 +60,7 @@ If you find this work helpful, please kindly cite our paper:
 ```bibtex
 @article{AttnRL,
     title   = {Attention as a Compass: Efficient Exploration for Process-Supervised RL in Reasoning Models},
-    author  = {Liu, Runze and Wang, Jiakang and Shi, Yuling and Xie, Zhihui and An, Chenxin and Zhang, Kaiyan and Zhao, Jian and Gu, Xiaodong and Lin, Lei and Hu, Wenping and others},
+    author  = {Liu, Runze and Wang, Jiakang and Shi, Yuling and Xie, Zhihui and An, Chenxin and Zhang, Kaiyan and Zhao, Jian and Gu, Xiaodong and Lin, Lei and Hu, Wenping and Li, Xiu and Zhang, Fuzheng and Zhou, Guorui and Gai, Kun},
     journal = {arXiv preprint arXiv:2509.26628},
     year    = {2025}
 }
@@ -33,5 +70,5 @@ If you find this work helpful, please kindly cite our paper:
 
 ## 💡 Acknowledgements
 
-Our code is based on [verl](https://github.com/volcengine/verl) and [TreeRL](https://github.com/THUDM/TreeRL).
-
+Our code is based on [verl](https://github.com/volcengine/verl) ([commit](https://github.com/volcengine/verl/commit/83ebd007e01de29bbe353de112d04245b4820b47)) and [TreeRL](https://github.com/THUDM/TreeRL).
+Our training dataset is from [DeepScaleR-Preview-Dataset](https://huggingface.co/datasets/agentica-org/DeepScaleR-Preview-Dataset) and rule-based verifier is based on [Skywork-OR1](https://github.com/SkyworkAI/Skywork-OR1), and [Archer](https://github.com/wizard-III/ArcherCodeR).