Update README.md

README.md

@@ -10,13 +10,21 @@ pretty_name: Molecule3D
 tags:
 - molecular geometry
 - molecular graph
-dataset_summary: Curated dataset of ground-state geometries of 4 million molecules
+dataset_summary: >-
+  Curated dataset of ground-state geometries of 4 million molecules
   dervied from density functional theory, consisting of SMILES, sdf, and 3D properties of molecules. 
   Random split and scaffold split datasets are uploaded to our repository.
-citation: "@inproceedings{huang2022frustratingly,\n  title={Frustratingly easy transferability\
-  \ estimation},\n  author={Huang, Long-Kai and Huang, Junzhou and Rong, Yu and Yang,\
-  \ Qiang and Wei, Ying},\n  booktitle={International Conference on Machine Learning},\n\
-  \  pages={9201--9225},\n  year={2022},\n  organization={PMLR}\n}"
+citation: >-
+  @misc{https://doi.org/10.48550/arxiv.2110.01717,
+  doi = {10.48550/ARXIV.2110.01717},
+  url = {https://arxiv.org/abs/2110.01717},
+  author = {Xu,  Zhao and Luo,  Youzhi and Zhang,  Xuan and Xu,  Xinyi and Xie,  Yaochen and Liu,  Meng and Dickerson,  Kaleb and Deng,  Cheng and Nakata,  Maho and Ji,  Shuiwang},
+  keywords = {Machine Learning (cs.LG),  Artificial Intelligence (cs.AI),  FOS: Computer and information sciences,  FOS: Computer and information sciences},
+  title = {Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs},
+  publisher = {arXiv},
+  year = {2021},
+  copyright = {arXiv.org perpetual,  non-exclusive license}
+  }
 configs:
 - config_name: Molecule3D_random_split
   data_files: