mlsanityData to 7 Oct 2026

Question-type Driven Question Generation

arXiv 1909.00140 ↗First posted 31 Aug 2019cs.CLcited by 16

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Abstract (arXiv)

Question generation is a challenging task which aims to ask a question based on an answer and relevant context. The existing works suffer from the mismatching between question type and answer, i.e. generating a question with type how while the answer is a personal name. We propose to automatically predict the question type based on the input answer and context. Then, the question type is fused into a seq2seq model to guide the question generation, so as to deal with the mismatching problem. We achieve significant improvement on the accuracy of question type prediction and finally obtain state-of-the-art results for question generation on both SQuAD and MARCO datasets.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Aug 2019.

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Citing papers per year: 2021: 4; 2022: 6; 2023: 3; 2024: 3.

16 papers.

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  1. 2021Controllable Open-ended Question Generation with A New Question Type Ontologycited by 36
  2. 2021MixQG: Neural Question Generation with Mixed Answer Typescited by 28
  3. 2024Leveraging Large Language Models for Learning Complex Legal Concepts through Storytellingcited by 23
  4. 2022Question Generation for Reading Comprehension Assessment by Modeling How and What to Askcited by 20
  5. 2022Towards Process-Oriented, Modular, and Versatile Question Generation that Meets Educational Needscited by 19
  6. 2021GTM: A Generative Triple-Wise Model for Conversational Question Generationcited by 16
  7. 2023Harnessing the Power of Prompt-based Techniques for Generating School-Level Questions using Large Language Modelscited by 9
  8. 2022"What makes a question inquisitive?" A Study on Type-Controlled Inquisitive Question Generationcited by 7
  9. 2022Downstream Transformer Generation of Question-Answer Pairs with Preprocessing and Postprocessing Pipelinescited by 5
  10. 2021Enhancing Question Generation with Commonsense Knowledgecited by 2
  11. 2022Unified Question Generation with Continual Lifelong Learningcited by 2
  12. 2023Automatic Generation of Multiple-Choice Questionscited by 2
4 more
  1. 2023Ask To The Point: Open-Domain Entity-Centric Question Generationcited by 2
  2. 2024Explicit Diversity Conditions for Effective Question Answer Generation with Large Language Modelscited by 2
  3. 2022On the Evaluation of Answer-Agnostic Paragraph-level Multi-Question Generationcited by 1
  4. 2024CAUS: A Dataset for Question Generation based on Human Cognition Leveraging Large Language Modelscited by 1