Update README.md

README.md

@@ -13,13 +13,23 @@ ViSoBERT is the state-of-the-art language model for Vietnamese social media task
 
 The general architecture and experimental results of ViSoBERT can be found in our [paper](https://arxiv.org/abs/2310.11166):
 
-    @misc{nguyen2023visobert,
-          title={ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing}, 
-          author={Quoc-Nam Nguyen and Thang Chau Phan and Duc-Vu Nguyen and Kiet Van Nguyen},
-          year={2023},
-          eprint={2310.11166},
-          archivePrefix={arXiv},
-          primaryClass={cs.CL}
+    @inproceedings{nguyen-etal-2023-visobert,
+        title = "{V}i{S}o{BERT}: A Pre-Trained Language Model for {V}ietnamese Social Media Text Processing",
+        author = "Nguyen, Nam  and
+          Phan, Thang  and
+          Nguyen, Duc-Vu  and
+          Nguyen, Kiet",
+        editor = "Bouamor, Houda  and
+          Pino, Juan  and
+          Bali, Kalika",
+        booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
+        month = dec,
+        year = "2023",
+        address = "Singapore",
+        publisher = "Association for Computational Linguistics",
+        url = "https://aclanthology.org/2023.emnlp-main.315",
+        pages = "5191--5207",
+        abstract = "English and Chinese, known as resource-rich languages, have witnessed the strong development of transformer-based language models for natural language processing tasks. Although Vietnam has approximately 100M people speaking Vietnamese, several pre-trained models, e.g., PhoBERT, ViBERT, and vELECTRA, performed well on general Vietnamese NLP tasks, including POS tagging and named entity recognition. These pre-trained language models are still limited to Vietnamese social media tasks. In this paper, we present the first monolingual pre-trained language model for Vietnamese social media texts, ViSoBERT, which is pre-trained on a large-scale corpus of high-quality and diverse Vietnamese social media texts using XLM-R architecture. Moreover, we explored our pre-trained model on five important natural language downstream tasks on Vietnamese social media texts: emotion recognition, hate speech detection, sentiment analysis, spam reviews detection, and hate speech spans detection. Our experiments demonstrate that ViSoBERT, with far fewer parameters, surpasses the previous state-of-the-art models on multiple Vietnamese social media tasks. Our ViSoBERT model is available only for research purposes. Disclaimer: This paper contains actual comments on social networks that might be construed as abusive, offensive, or obscene.",
     }
     
 The pretraining dataset of our paper is available at: [Pretraining dataset](https://drive.google.com/drive/folders/1C144LOlkbH78m0-JoMckpRXubV7XT7Kb)