Update README.md

README.md

@@ -5,4 +5,43 @@ language:
 base_model:
 - meta-llama/Meta-Llama-3-8B-Instruct
 library_name: transformers
----
+---
+
+# 🧠 LLM-QE: Improving Query Expansion by Aligning Large Language Models with Ranking Preferences
+
+This is the official model for **[LLM-QE: Improving Query Expansion by Aligning Large Language Models with Ranking Preferences](https://arxiv.org/abs/2502.17057)**.  
+
+## Model Description
+The LLM-QE model is designed to enhance **query expansion** in **information retrieval** tasks by leveraging **Large Language Models (LLMs)**, improving the **alignment between LLMs and ranking preferences** during query expansion.
+
+---
+
+## 📄 **Paper**
+For a detailed explanation of the methodology and experiments, please refer to our paper:  
+[**LLM-QE: Improving Query Expansion by Aligning Large Language Models with Ranking Preferences**](https://arxiv.org/abs/2502.17057)
+
+---
+
+## 🔄 Reproduce the Results
+To reproduce the experiments and benchmarks from the paper, follow the instructions provided in the official GitHub repository:
+
+[👉 GitHub: NEUIR/LLM-QE](https://github.com/NEUIR/LLM-QE).
+
+## 🛠 Model Details
+- Model Name: LLM-QE-DPO
+- Architecture: LLaMA3-8B-Instruct with query expansion alignment using ranking preferences
+
+## 🔖 Citation
+If you use LLM-QE in your work, please consider citing our paper:
+```
+@misc{yao2025llmqeimprovingqueryexpansion,
+      title={LLM-QE: Improving Query Expansion by Aligning Large Language Models with Ranking Preferences}, 
+      author={Sijia Yao and Pengcheng Huang and Zhenghao Liu and Yu Gu and Yukun Yan and Shi Yu and Ge Yu},
+      year={2025},
+      eprint={2502.17057},
+      archivePrefix={arXiv},
+      primaryClass={cs.IR},
+      url={https://arxiv.org/abs/2502.17057}, 
+}
+
+```