# Sentence Extraction-Based Machine Reading Comprehension for Vietnamese

arXiv: https://arxiv.org/abs/2105.09043 · HTML: https://mlsanity.com/paper/2105.09043/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 27 references that are in the map.
- First posted on arXiv 19 May 2021.

## Builds on (most cited first, 17 of 17)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://mlsanity.com/paper/1606.05250/) (2016)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Dense Passage Retrieval for Open-Domain Question Answering](https://mlsanity.com/paper/2004.04906/) (2020)
- [Reading Wikipedia to Answer Open-Domain Questions](https://mlsanity.com/paper/1704.00051/) (2017)
- [QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension](https://mlsanity.com/paper/1804.09541/) (2018)
- [PhoBERT: Pre-trained language models for Vietnamese](https://mlsanity.com/paper/2003.00744/) (2020)
- [A Span-Extraction Dataset for Chinese Machine Reading Comprehension](https://mlsanity.com/paper/1810.07366/) (2018)
- [BERT with History Answer Embedding for Conversational Question Answering](https://mlsanity.com/paper/1905.05412/) (2019)
- [FQuAD: French Question Answering Dataset](https://mlsanity.com/paper/2002.06071/) (2020)
- [VnCoreNLP: A Vietnamese Natural Language Processing Toolkit](https://mlsanity.com/paper/1801.01331/) (2018)
- [KorQuAD1.0: Korean QA Dataset for Machine Reading Comprehension](https://mlsanity.com/paper/1909.07005/) (2019)
- [SberQuAD -- Russian Reading Comprehension Dataset: Description and Analysis](https://mlsanity.com/paper/1912.09723/) (2019)
- [A Pilot Study of Text-to-SQL Semantic Parsing for Vietnamese](https://mlsanity.com/paper/2010.01891/) (2020)
- [A Vietnamese Dataset for Evaluating Machine Reading Comprehension](https://mlsanity.com/paper/2009.14725/) (2020)
- [New Vietnamese Corpus for Machine Reading Comprehension of Health News Articles](https://mlsanity.com/paper/2006.11138/) (2020)
- [BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels](https://mlsanity.com/paper/1910.05040/) (2019)

## Built on by (most cited first, 9 of 9)

- [VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding](https://mlsanity.com/paper/2403.15882/) (2024)
- [ViMMRC 2.0 -- Enhancing Machine Reading Comprehension on Vietnamese Literature Text](https://mlsanity.com/paper/2303.18162/) (2023)
- [XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Source](https://mlsanity.com/paper/2204.07002/) (2022)
- [R2GQA: Retriever-Reader-Generator Question Answering System to Support Students Understanding Legal Regulations in Higher Education](https://mlsanity.com/paper/2409.02840/) (2024)
- [AmQA: Amharic Question Answering Dataset](https://mlsanity.com/paper/2303.03290/) (2023)
- [VlogQA: Task, Dataset, and Baseline Models for Vietnamese Spoken-Based Machine Reading Comprehension](https://mlsanity.com/paper/2402.02655/) (2024)
- [ViLLM-Eval: A Comprehensive Evaluation Suite for Vietnamese Large Language Models](https://mlsanity.com/paper/2404.11086/) (2024)
- [ViQA-COVID: COVID-19 Machine Reading Comprehension Dataset for Vietnamese](https://mlsanity.com/paper/2504.21017/) (2025)
- [A Benchmark Dataset and Evaluation Framework for Vietnamese Large Language Models in Customer Support](https://mlsanity.com/paper/2507.22542/) (2025)

## Abstract (arXiv)

The development of natural language processing (NLP) in general and machine reading comprehension in particular has attracted the great attention of the research community. In recent years, there are a few datasets for machine reading comprehension tasks in Vietnamese with large sizes, such as UIT-ViQuAD and UIT-ViNewsQA. However, the datasets are not diverse in answers to serve the research. In this paper, we introduce UIT-ViWikiQA, the first dataset for evaluating sentence extraction-based machine reading comprehension in the Vietnamese language. The UIT-ViWikiQA dataset is converted from the UIT-ViQuAD dataset, consisting of comprises 23.074 question-answers based on 5.109 passages of 174 Wikipedia Vietnamese articles. We propose a conversion algorithm to create the dataset for sentence extraction-based machine reading comprehension and three types of approaches for sentence extraction-based machine reading comprehension in Vietnamese. Our experiments show that the best machine model is XLM-R_Large, which achieves an exact match (EM) of 85.97% and an F1-score of 88.77% on our dataset. Besides, we analyze experimental results in terms of the question type in Vietnamese and the effect of context on the performance of the MRC models, thereby showing the challenges from the UIT-ViWikiQA dataset that we propose to the language processing community.