Update README.md

README.md

@@ -17,7 +17,7 @@ This model is fine-tuned on top of `sentence-transformers/all-mpnet-base-v2` to
 
 ### Research Background
 
-As explained in our [EMNLP 2024 paper](https://example-link-to-paper), this model was fine-tuned using contrastive learning on human-generated arguments for and against various claims. This technique enhances sentence transformers' ability to capture sentiment and stance in opinionated texts while retaining computational efficiency over classification-based approaches.
+As explained in our [EMNLP 2024 paper](https://scholar.google.com/citations?view_op=view_citation&hl=en&user=RnPFjYcAAAAJ&citation_for_view=RnPFjYcAAAAJ:W7OEmFMy1HYC), this model was fine-tuned using contrastive learning on human-generated arguments for and against various claims. This technique enhances sentence transformers' ability to capture sentiment and stance in opinionated texts while retaining computational efficiency over classification-based approaches.
 
 ## Model Use and Code Instructions
 
@@ -29,7 +29,7 @@ Since this model leverages LoRA (Low-Rank Adaptation) fine-tuning, you only need
 First, ensure you have the required libraries installed:
 
 ```bash
-pip install peft transformers sentence-transformers torch
+!pip install peft transformers sentence-transformers torch
 
 
 from transformers import AutoModel, AutoTokenizer