Update README.md

README.md

@@ -11,8 +11,19 @@ language: mr
 
 # MahaSBERT-STS
 
-A MahaSBERT model (l3cube-pune/marathi-sentence-bert-nli) fine-tuned on STS dataset.
-This is released as a part of project MahaNLP : https://github.com/l3cube-pune/MarathiNLP
+A MahaSBERT model (l3cube-pune/marathi-sentence-bert-nli) fine-tuned on STS dataset. <br>
+This is released as a part of project MahaNLP : https://github.com/l3cube-pune/MarathiNLP <br>
+
+More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2211.11187) 
+
+```
+@article{joshi2022l3cubemahasbert,
+  title={L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi},
+  author={Joshi, Ananya and Kajale, Aditi and Gadre, Janhavi and Deode, Samruddhi and Joshi, Raviraj},
+  journal={arXiv preprint arXiv:2211.11187},
+  year={2022}
+}
+
 
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
@@ -74,7 +85,3 @@ sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']
 print("Sentence embeddings:")
 print(sentence_embeddings)
 ```
-
-## Citing & Authors
-
-It will be updated soon, refer to the project page for now.