mlsanityData to 7 Oct 2026

ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing

arXiv 2310.11166 ↗First posted 17 Oct 2023cs.CLcited by 11

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Abstract (arXiv)

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.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 29 of its 41 references that are in the map. First posted on arXiv 17 Oct 2023.

Builds on

29 of 41 references.

References · 29

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17 more
  1. 2022Should You Mask 15% in Masked Language Modeling?cited by 117
  2. 2021XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyondcited by 114
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  17. 2022Detecting Spam Reviews on Vietnamese E-commerce Websitescited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 4; 2026: 3.

11 papers.