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January 1, 2017Open Access

Machine Comprehension by Text-to-Text Neural Question Generation

XYXingdi YuanMicrosoft (United States)TWTong WangShanghai Ocean University ÇGÇağlar GülçehreÉcole Polytechnique Fédérale de Lausanne

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Resumen

Xingdi Yuan, Tong Wang, Caglar Gulcehre, Alessandro Sordoni, Philip Bachman, Saizheng Zhang, Sandeep Subramanian, Adam Trischler. Proceedings of the 2nd Workshop on Representation Learning for NLP. 2017.

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Cite This Study

Yuan et al. (Sun,) studied this question.

synapsesocial.com/papers/6a15608d9b87f33fc69f810b https://doi.org/https://doi.org/10.18653/v1/w17-2603

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1RevUP: Automatic Gap-Fill Question Generation from Educational Texts2015 · 50 citations
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3Active Comprehension: Problem-Solving Schema with Question Generation for Comprehension of Complex Short Stories1982 · 208 citations
4Good Question! Statistical Ranking for Question Generation2018 · 399 citations
5Sequence Level Training with Recurrent Neural Networks2016 · 671 citations

Comprensión de Máquinas mediante Generación de Preguntas Neurales de Texto a Texto | Synapse