Update README.md

README.md

@@ -14,7 +14,7 @@ tags:
 
 VHHBERT is a RoBERTa-based model pre-trained on two million VHH sequences in [VHHCorpus-2M](https://huggingface.co/datasets/COGNANO/VHHCorpus-2M).
 VHHBERT has the same model parameters as RoBERTa<sub>BASE</sub>, except that it used positional embeddings with a length of 185 to cover the maximum sequence length of 179 in VHHCorpus-2M.
-Further details on VHHBERT are described in our paper "A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models.”
+Further details on VHHBERT are described in our paper "[A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models](https://arxiv.org/abs/2405.18749).”
 
 ## Usage
 
@@ -30,12 +30,17 @@ model = RobertaModel.from_pretrained("tsurubee/VHHBERT")
 
 - Pre-training Corpus: https://huggingface.co/datasets/COGNANO/VHHCorpus-2M
 - Code: https://github.com/cognano/AVIDa-SARS-CoV-2
-- Paper: TBD
+- Paper: https://arxiv.org/abs/2405.18749
 
 ## Citation
 
 If you use VHHBERT in your research, please cite the following paper.
 
 ```bibtex
-TBD
+@article{tsuruta2024sars,
+  title={A {SARS}-{C}o{V}-2 Interaction Dataset and {VHH} Sequence Corpus for Antibody Language Models},
+  author={Hirofumi Tsuruta and Hiroyuki Yamazaki and Ryota Maeda and Ryotaro Tamura and Akihiro Imura},
+  journal={arXiv preprint arXiv:2405.18749},
+  year={2024}
+}
 ```