mlsanityData to 14 Oct 2026

Conversational Machine Reading Comprehension for Vietnamese Healthcare Texts

arXiv 2105.01542 ↗First posted 4 May 2021cs.CLcited by 7

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Abstract (arXiv)

Machine reading comprehension (MRC) is a sub-field in natural language processing that aims to assist computers understand unstructured texts and then answer questions related to them. In practice, the conversation is an essential way to communicate and transfer information. To help machines understand conversation texts, we present UIT-ViCoQA, a new corpus for conversational machine reading comprehension in the Vietnamese language. This corpus consists of 10,000 questions with answers over 2,000 conversations about health news articles. Then, we evaluate several baseline approaches for conversational machine comprehension on the UIT-ViCoQA corpus. The best model obtains an F1 score of 45.27%, which is 30.91 points behind human performance (76.18%), indicating that there is ample room for improvement. Our dataset is available at our website: http://nlp.uit.edu.vn/datasets/ for research purposes.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 19 of its 29 references that are in the map. First posted on arXiv 4 May 2021.

Builds on

19 of 29 references.

References · 19

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7 more
  1. 2020Open-Retrieval Conversational Question Answeringcited by 99
  2. 2019GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehensioncited by 41
  3. 2018SDNet: Contextualized Attention-based Deep Network for Conversational Question Answeringcited by 30
  4. 2020A Vietnamese Dataset for Evaluating Machine Reading Comprehensioncited by 30
  5. 2020New Vietnamese Corpus for Machine Reading Comprehension of Health News Articlescited by 23
  6. 2020Conversational Machine Comprehension: a Literature Reviewcited by 10
  7. 2019Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worldscited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 0; 2025: 2; 2026: 1.

7 papers.

  1. 2022VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehensioncited by 7
  2. 2023ViMMRC 2.0 -- Enhancing Machine Reading Comprehension on Vietnamese Literature Textcited by 5
  3. 2022UIT-ViCoV19QA: A Dataset for COVID-19 Community-based Question Answering on Vietnamese Languagecited by 4
  4. 2023Generative Pre-trained Transformer for Vietnamese Community-based COVID-19 Question Answeringcited by 1
  5. 2025A Vietnamese Dataset for Text Segmentation and Multiple Choices Reading Comprehensioncited by 0
  6. 2025A Benchmark Dataset and Evaluation Framework for Vietnamese Large Language Models in Customer Supportcited by 0
  7. 2026ViMultiChoice: Toward a Method That Gives Explanation for Multiple-Choice Reading Comprehension in Vietnamesecited by 0