Upload README.md

README.md

@@ -43,12 +43,17 @@ We use the GeoQA, UniGeo, Geometry3K, and PGPS9K datasets for fine-tuning and ev
 3. **Geometry3K and PGPS9K**: Follow the instructions [here](https://github.com/mingliangzhang2018/PGPS) to download the `PGPS9K` datasets. The `Geometry3K` is also provided in this database.
 
 
-<font color="#dd0000">Note:</font> Due to copyright restrictions, we are currently only providing links for these datasets. Full datasets for tuning and evaluation organized by us will be provided via email. If you need it, please contact us by [email](mailto:limc22@m.fudan.edu.cn).
+<font color="#dd0000">Note:</font> Due to copyright restrictions, we are currently only providing links for these datasets. Full datasets for tuning and evaluation organized by us will be provided via email. If you need it, please contact us by [email](bo.zhangzx@gmail.com).
 
 
 For more details, please refer to [our paper]() and [GitHub repository](https://github.com/UniModal4Reasoning/GeoX). If you find our work helpful, please consider starring ⭐ in this repository and citing us:
 
 ```bibtex
-
+@article{xia2024geox,
+  title={GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-training},
+  author={Xia, Renqiu and Li, Mingsheng and Ye, Hancheng and Wu, Wenjie and Zhou, Hongbin and Yuan, Jiakang and Peng, Tianshuo and Cai, Xinyu and Yan, Xiangchao and Wang, Bin and others},
+  journal={arXiv preprint arXiv:2412.11863},
+  year={2024}
+}
 ```