Update README.md

README.md

@@ -92,9 +92,19 @@ Each model's memory footprint can be anticipated by the qunatization docs in eit
 - Research supported with Cloud TPUs from [Google's TensorFlow Research Cloud](https://sites.research.google/trc/about/) (TFRC). Thanks for providing access to the TFRC ❤️
 - Thanks to the generous support from the Hugging Face team, it is possible to download models from their S3 storage 🤗
 
-## Contact
-*Feel free to contact us whenever you confront any problems :)*
+# Citation
+```bibtex
+@inproceedings{kesgin2024optimizing,
+  title={Optimizing Large Language Models for Turkish: New Methodologies in Corpus Selection and Training},
+  author={Kesgin, H Toprak and Yuce, M Kaan and Dogan, Eren and Uzun, M Egemen and Uz, Atahan and {\.I}nce, Elif and Erdem, Yusuf and Shbib, Osama and Zeer, Ahmed and Amasyali, M Fatih},
+  booktitle={2024 Innovations in Intelligent Systems and Applications Conference (ASYU)},
+  pages={1--6},
+  year={2024},
+  organization={IEEE}
+}
+```
 
+## Contact
 COSMOS AI Research Group, Yildiz Technical University Computer Engineering Department  
 https://cosmos.yildiz.edu.tr/  
 [email protected]