Updated README.md

README.md

@@ -10,7 +10,7 @@ license: other
 # MaterialsBERT
 
 This model is a fine-tuned version of [PubMedBERT model](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on a dataset of 2.4 million materials science abstracts.
-It was introduced in [this](https://arxiv.org/abs/2209.13136) paper. This model is uncased.
+It was introduced in [this](https://www.nature.com/articles/s41524-023-01003-w) paper. This model is uncased.
 
 ## Model description
 
@@ -70,11 +70,15 @@ The following hyperparameters were used during training:
 If you find MaterialsBERT useful in your research, please cite the following paper:
 
 ```latex
-@misc{materialsbert,
-  author = {Pranav Shetty, Arunkumar Chitteth Rajan, Christopher Kuenneth, Sonkakshi Gupta, Lakshmi Prerana Panchumarti, Lauren Holm, Chao Zhang, and Rampi Ramprasad},
-  title = {A general-purpose material property data extraction pipeline from large polymer corpora using Natural Language Processing},
-  year = {2022},
-  eprint = {arXiv:2209.13136},
+@article{materialsbert,
+  title={A general-purpose material property data extraction pipeline from large polymer corpora using natural language processing},
+  author={Shetty, Pranav and Rajan, Arunkumar Chitteth and Kuenneth, Chris and Gupta, Sonakshi and Panchumarti, Lakshmi Prerana and Holm, Lauren and Zhang, Chao and Ramprasad, Rampi},
+  journal={npj Computational Materials},
+  volume={9},
+  number={1},
+  pages={52},
+  year={2023},
+  publisher={Nature Publishing Group UK London}
 }
 ```