# A Vietnamese Dataset for Evaluating Machine Reading Comprehension

arXiv: https://arxiv.org/abs/2009.14725 · HTML: https://mlsanity.com/paper/2009.14725/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Sep 2020.

## Built on by (most cited first, 30 of 30)

- [QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension](https://mlsanity.com/paper/2107.12708/) (2021)
- [SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages](https://mlsanity.com/paper/2406.10118/) (2024)
- [CaLMQA: Exploring culturally specific long-form question answering across 23 languages](https://mlsanity.com/paper/2406.17761/) (2024)
- [ViDeBERTa: A powerful pre-trained language model for Vietnamese](https://mlsanity.com/paper/2301.10439/) (2023)
- [Sentence Extraction-Based Machine Reading Comprehension for Vietnamese](https://mlsanity.com/paper/2105.09043/) (2021)
- [VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding](https://mlsanity.com/paper/2403.15882/) (2024)
- [Conversational Machine Reading Comprehension for Vietnamese Healthcare Texts](https://mlsanity.com/paper/2105.01542/) (2021)
- [A cost-benefit analysis of cross-lingual transfer methods](https://mlsanity.com/paper/2105.06813/) (2021)
- [VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehension](https://mlsanity.com/paper/2203.11400/) (2022)
- [On the ability of monolingual models to learn language-agnostic representations](https://mlsanity.com/paper/2109.01942/) (2021)
- [A Survey on non-English Question Answering Dataset](https://mlsanity.com/paper/2112.13634/) (2021)
- [ViMMRC 2.0 -- Enhancing Machine Reading Comprehension on Vietnamese Literature Text](https://mlsanity.com/paper/2303.18162/) (2023)
- [TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya](https://mlsanity.com/paper/2404.17194/) (2024)
- [VN-MTEB: Vietnamese Massive Text Embedding Benchmark](https://mlsanity.com/paper/2507.21500/) (2025)
- [UIT-ViCoV19QA: A Dataset for COVID-19 Community-based Question Answering on Vietnamese Language](https://mlsanity.com/paper/2209.06668/) (2022)
- [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)
- [Span Detection for Aspect-Based Sentiment Analysis in Vietnamese](https://mlsanity.com/paper/2110.07833/) (2021)
- [Generative Pre-trained Transformer for Vietnamese Community-based COVID-19 Question Answering](https://mlsanity.com/paper/2310.14602/) (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)
- [A Large-Scale Benchmark for Vietnamese Sentence Paraphrases](https://mlsanity.com/paper/2502.07188/) (2025)
- [Advancing Vietnamese Information Retrieval with Learning Objective and Benchmark](https://mlsanity.com/paper/2503.07470/) (2025)
- [Integrating Semantic Information into Sketchy Reading Module of Retro-Reader for Vietnamese Machine Reading Comprehension](https://mlsanity.com/paper/2301.00429/) (2023)
- [Integrating Image Features with Convolutional Sequence-to-sequence Network for Multilingual Visual Question Answering](https://mlsanity.com/paper/2303.12671/) (2023)
- [Revealing Weaknesses of Vietnamese Language Models Through Unanswerable Questions in Machine Reading Comprehension](https://mlsanity.com/paper/2303.13355/) (2023)
- [ViQA-COVID: COVID-19 Machine Reading Comprehension Dataset for Vietnamese](https://mlsanity.com/paper/2504.21017/) (2025)
- [A Vietnamese Dataset for Text Segmentation and Multiple Choices Reading Comprehension](https://mlsanity.com/paper/2506.15978/) (2025)
- [A Benchmark Dataset and Evaluation Framework for Vietnamese Large Language Models in Customer Support](https://mlsanity.com/paper/2507.22542/) (2025)
- [ViMultiChoice: Toward a Method That Gives Explanation for Multiple-Choice Reading Comprehension in Vietnamese](https://mlsanity.com/paper/2602.09961/) (2026)

## Abstract (arXiv)

Over 97 million people speak Vietnamese as their native language in the world. However, there are few research studies on machine reading comprehension (MRC) for Vietnamese, the task of understanding a text and answering questions related to it. Due to the lack of benchmark datasets for Vietnamese, we present the Vietnamese Question Answering Dataset (UIT-ViQuAD), a new dataset for the low-resource language as Vietnamese to evaluate MRC models. This dataset comprises over 23,000 human-generated question-answer pairs based on 5,109 passages of 174 Vietnamese articles from Wikipedia. In particular, we propose a new process of dataset creation for Vietnamese MRC. Our in-depth analyses illustrate that our dataset requires abilities beyond simple reasoning like word matching and demands single-sentence and multiple-sentence inferences. Besides, we conduct experiments on state-of-the-art MRC methods for English and Chinese as the first experimental models on UIT-ViQuAD. We also estimate human performance on the dataset and compare it to the experimental results of powerful machine learning models. As a result, the substantial differences between human performance and the best model performance on the dataset indicate that improvements can be made on UIT-ViQuAD in future research. Our dataset is freely available on our website to encourage the research community to overcome challenges in Vietnamese MRC.