Datasets:
metadata
license: cc
language:
- vi
- en
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: pubmed
dataset_info:
features:
- name: en
dtype: string
- name: vi
dtype: string
splits:
- name: pubmed22
num_bytes: 44360028980
num_examples: 20087006
download_size: 23041004247
dataset_size: 44360028980
Dataset Summary
20M Vietnamese PubMed biomedical abstracts translated by the state-of-the-art English-Vietnamese Translation project. The data has been used as unlabeled dataset for pretraining a Vietnamese Biomedical-domain Transformer model.
image source: Enriching Biomedical Knowledge for Vietnamese Low-resource Language Through Large-Scale Translation
Language
- English: Original biomedical abstracts from Pubmed
- Vietnamese: Synthetic abstract translated by a state-of-the-art English-Vietnamese Translation project
Dataset Structure
- The English sequences are
- The Vietnamese sequences are
Source Data - Initial Data Collection and Normalization
https://www.nlm.nih.gov/databases/download/pubmed_medline_faq.html
Licensing Information
Courtesy of the U.S. National Library of Medicine.
Citation
@misc{mtet,
doi = {10.48550/ARXIV.2210.05610},
url = {https://arxiv.org/abs/2210.05610},
author = {Ngo, Chinh and Trinh, Trieu H. and Phan, Long and Tran, Hieu and Dang, Tai and Nguyen, Hieu and Nguyen, Minh and Luong, Minh-Thang},
keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {MTet: Multi-domain Translation for English and Vietnamese},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}
@misc{vipubmed,
doi = {10.48550/ARXIV.2210.05598},
url = {https://arxiv.org/abs/2210.05598},
author = {Phan, Long and Dang, Tai and Tran, Hieu and Phan, Vy and Chau, Lam D. and Trinh, Trieu H.},
keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Enriching Biomedical Knowledge for Vietnamese Low-resource Language Through Large-Scale Translation},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}