Learning to Ask: Neural Question Generation for Reading Comprehension
Xinya Du,Junru Shao,Claire Cardie +2 more
- Vol. 1, pp 1342-1352
TLDR
This paper proposed an attention-based sequence learning model for question generation from text passages in reading comprehension, which is trainable end-to-end via sequence-tosequence learning and significantly outperforms the state-of-the-art rule-based system.Abstract:
We study automatic question generation for sentences from text passages in reading comprehension. We introduce an attention-based sequence learning model for the task and investigate the effect of encoding sentence- vs. paragraph-level information. In contrast to all previous work, our model does not rely on hand-crafted rules or a sophisticated NLP pipeline; it is instead trainable end-to-end via sequence-to-sequence learning. Automatic evaluation results show that our system significantly outperforms the state-of-the-art rule-based system. In human evaluations, questions generated by our system are also rated as being more natural (i.e.,, grammaticality, fluency) and as more difficult to answer (in terms of syntactic and lexical divergence from the original text and reasoning needed to answer).read more
Citations
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Fluent Response Generation for Conversational Question Answering
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Intelligence Is Asking The Right Question: A Study On Japanese Question Generation
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TL;DR: Automatic evaluation results show that the system outperforms the state-of-the-art rule-based system, and also excels in terms of content quality and fluency according to a subjective human test.
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TL;DR: This article proposed a recurrent generative model that generates multiple keyphrases as delimiter-separated sequences and further enhances the diversity by manipulating decoder hidden states to control the number of outputs.
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Automatic Question Generation System for English Reading Comprehension
TL;DR: A web-based automatic question generation (AQG) system to generate reading comprehension questions and multiple-choice questions on grammar from a given English text is presented, revealing the effectiveness of the system for teachers and parents.
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Building an Agent for Factual Question Generation Task
Miroslav Blšták,Viera Rozinajová +1 more
TL;DR: The endeavour to design and create an interactive educational agent which to some extent acts as a teacher: it automatically generates factual questions from the educational text and tries to reveal if the student understood the information presented there.
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