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--- |
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task_categories: |
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- summarization |
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- feature-extraction |
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language: |
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- vi |
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pretty_name: Vietnamese NewsSapo Dataset |
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size_categories: |
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- 10M<n<100M |
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--- |
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Vietnamese NewsSapo Dataset |
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The Vietnamese NewsSapo dataset was constructed to train sentence/passage embeddings. Our dataset is structured in a "title-abstract-contents" format, where each news article is represented by a tuple of (title, abstract, content). The content is the main text body of the article and has been processed to remove images, videos, and other non-textual elements. The dataset contains 31,728,183 triples. |
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To build this dataset, we followed a two-step process: |
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Step 1: Collect news data from 2021-11/2023. Combine with [Binhvq News Corpus](https://github.com/binhvq/news-corpus) to form a unified dataset. |
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Step 2: Extract title-sapo-content for each article. |
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### Please cite our manuscript if this dataset is used for your work |
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``` |
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@article{duc2024towards, |
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title={Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models}, |
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author={Nguyen Quang Duc, Le Hai Son, Nguyen Duc Nhan, Nguyen Dich Nhat Minh, Le Thanh Huong, Dinh Viet Sang}, |
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journal={arXiv preprint arXiv:2403.01616}, |
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year={2024} |
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} |
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``` |
