Papers by Lauren Lutz Coleman

1 papers
Question Generation for Reading Comprehension Assessment by Modeling How and What to Ask (2022.findings-acl)

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Challenge: Existing Question Generation systems focus on extractive questions and do not control the type of questions.
Approach: They propose a question generation model that generates inferential questions from text . they propose he model can generate questions annotated with story-based reading comprehension skills .
Outcome: The proposed model outperforms baselines on a reading comprehension dataset.

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