mlsanityData to 7 Oct 2026

AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents

arXiv 2103.03820 ↗First posted 5 Mar 2021cs.CLcited by 4

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Abstract (arXiv)

One strategy for facilitating reading comprehension is to present information in a question-and-answer format. We demo a system that integrates the tasks of question answering (QA) and question generation (QG) in order to produce Q&A items that convey the content of multi-paragraph documents. We report some experiments for QA and QG that yield improvements on both tasks, and assess how they interact to produce a list of Q&A items for a text. The demo is accessible at qna.sdl.com.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 19 of its 31 references that are in the map. First posted on arXiv 5 Mar 2021.

Builds on

19 of 31 references.

References · 19

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
  3. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  4. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,898
  5. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  6. 2016NewsQA: A Machine Comprehension Datasetcited by 330
  7. 2016Bidirectional Attention Flow for Machine Comprehensioncited by 278
  8. 2017OpenNMT: Open-source Toolkit for Neural Machine Translationcited by 251
  9. 2017Learning to Ask: Neural Question Generation for Reading Comprehensioncited by 186
  10. 2019End-to-End Open-Domain Question Answering with BERTserinicited by 152
  11. 2017Simple and Effective Multi-Paragraph Reading Comprehensioncited by 120
  12. 2019Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answeringcited by 96
7 more
  1. 2019Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answeringcited by 63
  2. 2019MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehensioncited by 60
  3. 2018Towards a Better Metric for Evaluating Question Generation Systemscited by 52
  4. 2017Machine Comprehension by Text-to-Text Neural Question Generationcited by 32
  5. 2019Generating Question-Answer Hierarchiescited by 20
  6. 2019Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehensioncited by 15
  7. 2019ParaQG: A System for Generating Questions and Answers from Paragraphscited by 2

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Cited by year

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

4 papers.

  1. 2022Question Generation for Reading Comprehension Assessment by Modeling How and What to Askcited by 20
  2. 2022Leaf: Multiple-Choice Question Generationcited by 9
  3. 2024Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future Trendscited by 3
  4. 2024FAQ-Gen: An automated system to generate domain-specific FAQs to aid content comprehensioncited by 2