Update README.md

README.md

@@ -1,17 +1,13 @@
 # AraT5-base
 # AraT5: Text-to-Text Transformers for Arabic Language Generation
 
-<img src="AraT5_CR_new.png" alt="AraT5" width="55%" height="45%" align="right"/>
+<img src="https://huggingface.co/UBC-NLP/AraT5-base/resolve/main/AraT5_CR_new.png" alt="AraT5" width="45%" height="35%" align="right"/>
 
 This is the repository accompanying our paper [AraT5: Text-to-Text Transformers for Arabic Language Understanding and Generation](https://arxiv.org/abs/2109.12068). In this is the repository we introduce:
 * Introduce **AraT5<sub>MSA</sub>**, **AraT5<sub>Tweet</sub>**, and **AraT5**: three powerful Arabic-specific text-to-text Transformer based models;
 * Introduce **ARGEN**:  A new benchmark for Arabic language generation and evaluation for four Arabic NLP tasks, namely, ```machine  translation```,  ```summarization```,  ```news title   generation```,   ```question   generation```, ,   ```paraphrasing```,   ```transliteration```, and  ```code-switched translation```.
 * Evaluate  ```AraT5``` models on ```ARGEN``` and compare against available language models.
 
-Our models establish new state-of-the-art (SOTA) on  several publicly available datasets.
-Our language models are publicaly available for research (see below).
-
-The rest of this repository provides more information about our new language models, benchmark, and experiments.
 
 ---
 # How to use AraT5 models
@@ -56,14 +52,16 @@ AraT5 Pytorch and TensorFlow checkpoints are available on the Huggingface websit
 
 If you use our models (Arat5-base, Arat5-msa-base, Arat5-tweet-base, Arat5-msa-small, or Arat5-tweet-small ) for your scientific publication, or if you find the resources in this repository useful, please cite our paper as follows (to be updated):
 ```bibtex
-@inproceedings{araT5-2021,
-    title = "{AraT5: Text-to-Text Transformers for Arabic Language Understanding and Generation",
+@inproceedings{nagoudi-2022-arat5,
+    title = "{AraT5: Text-to-Text Transformers for Arabic Language Generation",
     author = "Nagoudi, El Moatez Billah  and
       Elmadany, AbdelRahim  and
       Abdul-Mageed, Muhammad",
-    booktitle = "https://arxiv.org/abs/2109.12068",
-    month = aug,
-    year = "2021"}
+    booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics",
+    month = May,
+    year = "2022",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
 ```
 
 ## Acknowledgments