Update README.md

README.md

@@ -4,6 +4,8 @@ license: apache-2.0
 
 The finetuned BART-Large based model is used to expand abstract sentences. Use the following demo code to generate diverse expansions from abstract inputs.
 
+# Code
+
 ```python
 from transformers import pipeline, AutoTokenizer
 tokenizer = AutoTokenizer.from_pretrained('utkarsh4430/ABEX-abstract-expand')
@@ -16,11 +18,22 @@ for f in range(5):
     print(f'Aug {f}: ', generated_text[0]['generated_text'])
 ```
 
-Example output:
+# Example output:
 ```
 Aug 0:  WWE stars to visit Detroit on January 20th for the second time in three years, with appearances at The Battle at the Fox Sports 1 World Headquarters, and proceeds going to a charity of your choice.
 Aug 1:  A one-on-one experience at the WWE Creative Conference in New Jersey was provided, with an opportunity for the audience to meet WWE superstars and support a good cause.
 Aug 2:  Sindrun welcomes WWE star Chris Jericho and hosts an event for attendees to meet WWE stars and support a local cause.
 Aug 3:  Find out if you can meet WWE stars, including the Rock and Shake, at a benefit luncheon.
 Aug 4:  The WWE Talent Showcase 2019 will feature exciting moments inside the WWE Studios, including the first one in over a decade, and features a chance to hug current and former stars and receive a check from a corporate sponsor.
+```
+
+# Citation instructions:
+```
+@inproceedings{
+ghosh2024abex,
+title={{ABEX}: Data Augmentation for Low-Resource {NLU} via Expanding Abstract Descriptions},
+author={Sreyan Ghosh and Utkarsh Tyagi and Sonal Kumar and Chandra Kiran Reddy Evuru and and Ramaneswaran S and S Sakshi and Dinesh Manocha},
+booktitle={The 62nd Annual Meeting of the Association for Computational Linguistics},
+year={2024},
+}
 ```