Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural Machine Reading Comprehension: Methods and Trends   Machine reading comprehension (MRC), which requires a machine to answer
questions based on a given context, has attracted increasing attention with the
incorporation of various deep-learning techniques over the past few years.
Although research on MRC based on deep learning is flourishing, there remains a
lack of a comprehensive survey summarizing existing approaches and recent
trends, which motivated the work presented in this article. Specifically, we
give a thorough review of this research field, covering different aspects
including (1) typical MRC tasks: their definitions, differences, and
representative datasets; (2) the general architecture of neural MRC: the main
modules and prevalent approaches to each; and (3) new trends: some emerging
areas in neural MRC as well as the corresponding challenges. Finally,
considering what has been achieved so far, the survey also envisages what the
future may hold by discussing the open issues left to be addressed.

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The categories of this paper are: solv-int
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The categories of this paper are: ao-sci
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The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: chem-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-th
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The categories of this paper are: physics
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The categories of this paper are: math-ph
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The categories of this paper are: nlin
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The categories of this paper are: stat
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The categories of this paper are: hep-lat
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The categories of this paper are: q-bio
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The categories of this paper are: bayes-an
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The categories of this paper are: adap-org