Update README.md

README.md

@@ -5,7 +5,7 @@ license: apache-2.0
 # MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
 
 <p align="center">
-📃 <a href="https://arxiv.org/" target="_blank">Paper</a> ｜🤗 <a href="https://huggingface.co/UCSC-VLAA/MedReason-8B" target="_blank">MedReason-8B</a> | 📚 <a href="https://huggingface.co/UCSC-VLAA/MedReason-8B" target="_blank">MedReason Data</a>
+📃 <a href="https://arxiv.org/abs/2504.00993" target="_blank">Paper</a> ｜🤗 <a href="https://huggingface.co/UCSC-VLAA/MedReason-8B" target="_blank">MedReason-8B</a> | 📚 <a href="https://huggingface.co/datasets/UCSC-VLAA/MedReason" target="_blank">MedReason Data</a>
 </p>
 
 
@@ -47,4 +47,23 @@ messages = [{"role": "user", "content": input_text}]
 inputs = tokenizer(tokenizer.apply_chat_template(messages, tokenize=False,add_generation_prompt=True), return_tensors="pt").to(model.device)
 outputs = model.generate(**inputs, max_new_tokens=2048)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
-```
+```
+
+## 🙏🏼 Acknowledgement
+
+We gratefully acknowledge the inspiring work of [HuatuoGPT-o1](https://github.com/FreedomIntelligence/HuatuoGPT-o1), which laid important groundwork for this research. We also thank the developers of the excellent tools [curator](https://github.com/bespokelabsai/curator/), [trl](https://github.com/huggingface/trl), and [sglang](https://github.com/sgl-project/sglang) for making this work possible.
+
+## 📖 Citation
+
+```
+@misc{wu2025medreasonelicitingfactualmedical,
+      title={MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs}, 
+      author={Juncheng Wu and Wenlong Deng and Xingxuan Li and Sheng Liu and Taomian Mi and Yifan Peng and Ziyang Xu and Yi Liu and Hyunjin Cho and Chang-In Choi and Yihan Cao and Hui Ren and Xiang Li and Xiaoxiao Li and Yuyin Zhou},
+      year={2025},
+      eprint={2504.00993},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2504.00993}, 
+}
+```
+