Update README.md

README.md

@@ -1,11 +1,30 @@
-The AraRoBERTa models are mono-dialectal Arabic models trained on a country-level dialect. AraRoBERTa uses RoBERTa base config. More details are available in the paper (soon).
+The AraRoBERTa models are mono-dialectal Arabic models trained on a country-level dialect. AraRoBERTa uses RoBERTa base config. More details are available in the paper [click](https://aclanthology.org/2022.wanlp-1.24/).
 
 The following are the AraRoBERTa seven dialectal variations:
 
 AraRoBERTa-SA: Saudi Arabia (SA).
-AraRoBERTa-EG: Egypt (EG).
+AraRoBERTa-EGY: Egypt (EGY).
 AraRoBERTa-KU: Kuwait (KU).
 AraRoBERTa-OM: Oman (OM).
 AraRoBERTa-LB: Lebanon (LB).
 AraRoBERTa-JO: Jordan (JO).
-AraRoBERTa-DZ: Algeria (DZ).
+AraRoBERTa-DZ: Algeria (DZ).
+
+# When using the model, please cite our paper:
+
+```python
+@inproceedings{alyami-al-zaidy-2022-weakly,
+    title = "Weakly and Semi-Supervised Learning for {A}rabic Text Classification using Monodialectal Language Models",
+    author = "AlYami, Reem  and Al-Zaidy, Rabah",
+    booktitle = "Proceedings of the The Seventh Arabic Natural Language Processing Workshop (WANLP)",
+    month = dec,
+    year = "2022",
+    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2022.wanlp-1.24",
+    pages = "260--272",
+}
+```
+
+# Contact
+**Reem AlYami**: [Linkedin](https://www.linkedin.com/in/reem-alyami/) | <reem.yami@kfupm.edu.sa> | <yami.m.reem@gmail.com>