vund commited on
Commit
d2650d0
1 Parent(s): e9ed184

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +17 -7
README.md CHANGED
@@ -13,13 +13,23 @@ ViSoBERT is the state-of-the-art language model for Vietnamese social media task
13
 
14
  The general architecture and experimental results of ViSoBERT can be found in our [paper](https://arxiv.org/abs/2310.11166):
15
 
16
- @misc{nguyen2023visobert,
17
- title={ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing},
18
- author={Quoc-Nam Nguyen and Thang Chau Phan and Duc-Vu Nguyen and Kiet Van Nguyen},
19
- year={2023},
20
- eprint={2310.11166},
21
- archivePrefix={arXiv},
22
- primaryClass={cs.CL}
 
 
 
 
 
 
 
 
 
 
23
  }
24
 
25
  The pretraining dataset of our paper is available at: [Pretraining dataset](https://drive.google.com/drive/folders/1C144LOlkbH78m0-JoMckpRXubV7XT7Kb)
 
13
 
14
  The general architecture and experimental results of ViSoBERT can be found in our [paper](https://arxiv.org/abs/2310.11166):
15
 
16
+ @inproceedings{nguyen-etal-2023-visobert,
17
+ title = "{V}i{S}o{BERT}: A Pre-Trained Language Model for {V}ietnamese Social Media Text Processing",
18
+ author = "Nguyen, Nam and
19
+ Phan, Thang and
20
+ Nguyen, Duc-Vu and
21
+ Nguyen, Kiet",
22
+ editor = "Bouamor, Houda and
23
+ Pino, Juan and
24
+ Bali, Kalika",
25
+ booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
26
+ month = dec,
27
+ year = "2023",
28
+ address = "Singapore",
29
+ publisher = "Association for Computational Linguistics",
30
+ url = "https://aclanthology.org/2023.emnlp-main.315",
31
+ pages = "5191--5207",
32
+ 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.",
33
  }
34
 
35
  The pretraining dataset of our paper is available at: [Pretraining dataset](https://drive.google.com/drive/folders/1C144LOlkbH78m0-JoMckpRXubV7XT7Kb)