Update README.md

README.md

@@ -15,7 +15,17 @@ https://arxiv.org/...
 Model architecture is similar to RoBERTa-base (12 layers, 12 heads, and 768 hidden size). Tokenization algorithm is WordPiece. Vocabulary size is 30k. 
 
 The details of pretraining can be found at this paper: 
-https://arxiv.org/...
+```bibtex
+@InProceedings{clef-checkthat:2022:task1:oguzhan,
+author = {Cagri Toraman and Oguzhan Ozcelik and Furkan Şahinuç and Umitcan Sahin},
+title = "{ARC-NLP at CheckThat! 2022:} Contradiction for Harmful Tweet Detection",
+year = {2022},
+booktitle = "Working Notes of {CLEF} 2022 - Conference and Labs of the Evaluation Forum",
+editor = {Faggioli, Guglielmo andd Ferro, Nicola and Hanbury, Allan and Potthast, Martin},
+series = {CLEF~'2022},
+address = {Bologna, Italy},
+}
+```
 
 The following code can be used for model loading and tokenization, example max length (768) can be changed:
 ```
@@ -36,5 +46,13 @@ The following code can be used for model loading and tokenization, example max l
 
 ### BibTeX entry and citation info
 ```bibtex
-@article{}
+@InProceedings{clef-checkthat:2022:task1:oguzhan,
+author = {Cagri Toraman and Oguzhan Ozcelik and Furkan Şahinuç and Umitcan Sahin},
+title = "{ARC-NLP at CheckThat! 2022:} Contradiction for Harmful Tweet Detection",
+year = {2022},
+booktitle = "Working Notes of {CLEF} 2022 - Conference and Labs of the Evaluation Forum",
+editor = {Faggioli, Guglielmo andd Ferro, Nicola and Hanbury, Allan and Potthast, Martin},
+series = {CLEF~'2022},
+address = {Bologna, Italy},
+}
 ```