Update README.md

README.md

@@ -7,33 +7,42 @@ tags:
 - social media
 - contrastive learning
 ---
-# Contrastive Learning of Sociopragmatic Meaning in Social Media
+# The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages
 
-<p align="center"> <a href="https://chiyuzhang94.github.io/" target="_blank">Chiyu Zhang</a>,  <a href="https://mageed.arts.ubc.ca/" target="_blank">Muhammad Abdul-Mageed</a>, <a href="https://ganeshjawahar.github.io/" target="_blank">Ganesh Jarwaha</a></p>
+<p align="center"> <a href="https://chiyuzhang94.github.io/" target="_blank">Chiyu Zhang</a>, Khai Duy Doan, Qisheng Liao, <a href="https://mageed.arts.ubc.ca/" target="_blank">Muhammad Abdul-Mageed</a></p>
 <p align="center" float="left">
-  
-<p align="center">Publish at Findings of ACL 2023</p>
 
-[![Code License](https://img.shields.io/badge/Code%20License-Apache_2.0-green.svg)]()
-[![Data License](https://img.shields.io/badge/Data%20License-CC%20By%20NC%204.0-red.svg)]()
+<p align="center" float="left">
+  The University of British Columbia, Mohamed bin Zayed University of Artificial Intelligence
+</p>
 
+<p align="center">Publish at Main Conference of EMNLP 2023</p>
+<p align="center"> <a href="https://arxiv.org/abs/2310.14557" target="_blank">Paper</a></p> 
 
-<p align="center" width="100%">
-    <a><img src="https://github.com/UBC-NLP/infodcl/blob/master/images/infodcl_vis.png?raw=true" alt="Title" style="width: 90%; min-width: 300px; display: block; margin: auto;"></a>
-</p>
-Illustration of our proposed InfoDCL framework. We exploit distant/surrogate labels (i.e., emojis) to supervise two contrastive losses, corpus-aware contrastive loss (CCL) and Light label-aware contrastive loss (LCL-LiT). Sequence representations from our model should keep the cluster of each class distinguishable and preserve semantic relationships between classes.
+[![Code License](https://img.shields.io/badge/Code%20License-Apache_2.0-green.svg)]()
+[![Data License](https://img.shields.io/badge/Data%20License-CC%20By%20NC%204.0-red.svg)]()
 
 ## Checkpoints of Models Pre-Trained with InfoDCL 
-Enlish Models:
-* InfoDCL-RoBERTa trained with TweetEmoji-EN: https://huggingface.co/UBC-NLP/InfoDCL-emoji 
-* InfoDCL-RoBERTa trained with TweetHashtag-EN: https://huggingface.co/UBC-NLP/InfoDCL-hashtag
+We further pretrained XLMR/RoBERTa with InfoDCL framework by ([Zhang et al. 2023](https://aclanthology.org/2023.findings-acl.152/))
 
 Multilingual Model:
 * InfoDCL-XLMR trained with multilingual TweetEmoji-multi: https://huggingface.co/UBC-NLP/InfoDCL-Emoji-XLMR-Base
 
-## Model Performance
+Enlish Models:
+* InfoDCL-RoBERTa trained with TweetEmoji-EN: https://huggingface.co/UBC-NLP/InfoDCL-emoji 
+* InfoDCL-RoBERTa trained with TweetHashtag-EN: https://huggingface.co/UBC-NLP/InfoDCL-hashtag
 
-<p align="center" width="100%">
-    <a><img src="https://github.com/UBC-NLP/infodcl/blob/master/images/main_table.png?raw=true" alt="main table" style="width: 95%; min-width: 300px; display: block; margin: auto;"></a>
-</p>
-Fine-tuning results on our 24 Socio-pragmatic Meaning datasets (average macro-F1 over five runs).
+## Citation
+Please cite us if you find our data or models useful.
+```bibtex
+@inproceedings{zhang-etal-2023-skipped,
+    title = "The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages",
+    author = "Zhang, Chiyu  and
+      Khai Duy Doan and,
+      Qisheng Liao and,
+      Abdul-Mageed, Muhammad",
+    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
+    year = "2023",
+    publisher = "Association for Computational Linguistics",
+}
+```