Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for
  Rewriting Ill-Formed Questions   We present a large-scale dataset for the task of rewriting an ill-formed
natural language question to a well-formed one. Our multi-domain question
rewriting MQR dataset is constructed from human contributed Stack Exchange
question edit histories. The dataset contains 427,719 question pairs which come
from 303 domains. We provide human annotations for a subset of the dataset as a
quality estimate. When moving from ill-formed to well-formed questions, the
question quality improves by an average of 45 points across three aspects. We
train sequence-to-sequence neural models on the constructed dataset and obtain
an improvement of 13.2% in BLEU-4 over baseline methods built from other data
resources. We release the MQR dataset to encourage research on the problem of
question rewriting.

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The categories of this paper are: eess
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The categories of this paper are: hep-ex
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The categories of this paper are: nucl-th
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The categories of this paper are: physics
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The categories of this paper are: solv-int
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The categories of this paper are: hep-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: gr-qc
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The categories of this paper are: math
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The categories of this paper are: acc-phys
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The categories of this paper are: supr-con
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The categories of this paper are: ao-sci
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: patt-sol