mlsanityData to 7 Oct 2026

CONSISTENT: Open-Ended Question Generation From News Articles

arXiv 2210.11536 ↗First posted 20 Oct 2022cs.CLcited by 6

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Abstract (arXiv)

Recent work on question generation has largely focused on factoid questions such as who, what, where, when about basic facts. Generating open-ended why, how, what, etc. questions that require long-form answers have proven more difficult. To facilitate the generation of open-ended questions, we propose CONSISTENT, a new end-to-end system for generating open-ended questions that are answerable from and faithful to the input text. Using news articles as a trustworthy foundation for experimentation, we demonstrate our model's strength over several baselines using both automatic and human=based evaluations. We contribute an evaluation dataset of expert-generated open-ended questions.We discuss potential downstream applications for news media organizations.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 34 of its 49 references that are in the map. First posted on arXiv 20 Oct 2022.

Builds on

34 of 49 references.

References · 34

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22 more
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Citing papers per year: 2022: 1; 2023: 3; 2024: 1; 2025: 1.

6 papers.