Update README.md

README.md

@@ -20,6 +20,8 @@ Welcome to IBM's series of large foundation models for sustainable materials. Ou
 
 GitHub: [GitHub Link](https://github.com/IBM/materials/tree/main)
 
+Paper: [arXiv:2407.20267](https://arxiv.org/abs/2407.20267)
+
 # SMILES-based Transformer Encoder-Decoder (SMI-TED)
 
 ![ted-smi](smi-ted.png)
@@ -167,4 +169,20 @@ For decoder, you can use the function, so you can return from embeddings to SMIL
 ```python
 with torch.no_grad():
     decoded_smiles = model.decode(encoded_embeddings)
-```
+```
+
+
+## Citations
+
+```
+@misc{soares2024largeencoderdecoderfamilyfoundation,
+      title={A Large Encoder-Decoder Family of Foundation Models For Chemical Language}, 
+      author={Eduardo Soares and Victor Shirasuna and Emilio Vital Brazil and Renato Cerqueira and Dmitry Zubarev and Kristin Schmidt},
+      year={2024},
+      eprint={2407.20267},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2407.20267}, 
+}
+
+```