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arXiv · 1510.07526

Empirical Study on Deep Learning Models for Question Answering

Yang Yu·Wei Zhang·Chung-Wei Hang·Bing Xiang·Bowen Zhou
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Abstract

In this paper we explore deep learning models with memory component or attention mechanism for question answering task. We combine and compare three models, Neural Machine Translation, Neural Turing Machine, and Memory Networks for a simulated QA data set. This paper is the first one that uses Neural Machine Translation and Neural Turing Machines for solving QA tasks. Our results suggest that the combination of attention and memory have potential to solve certain QA problem.

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Yang Yu, Wei Zhang, Chung-Wei Hang, Bing Xiang, Bowen Zhou. 2015-10-26. Empirical Study on Deep Learning Models for Question Answering. https://arxiv.org/abs/1510.07526

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