Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Joint Learning of Answer Selection and Answer Summary Generation in
  Community Question Answering   Community question answering (CQA) gains increasing popularity in both
academy and industry recently. However, the redundancy and lengthiness issues
of crowdsourced answers limit the performance of answer selection and lead to
reading difficulties and misunderstandings for community users. To solve these
problems, we tackle the tasks of answer selection and answer summary generation
in CQA with a novel joint learning model. Specifically, we design a
question-driven pointer-generator network, which exploits the correlation
information between question-answer pairs to aid in attending the essential
information when generating answer summaries. Meanwhile, we leverage the answer
summaries to alleviate noise in original lengthy answers when ranking the
relevancy degrees of question-answer pairs. In addition, we construct a new
large-scale CQA corpus, WikiHowQA, which contains long answers for answer
selection as well as reference summaries for answer summarization. The
experimental results show that the joint learning method can effectively
address the answer redundancy issue in CQA and achieves state-of-the-art
results on both answer selection and text summarization tasks. Furthermore, the
proposed model is shown to be of great transferring ability and applicability
for resource-poor CQA tasks, which lack of reference answer summaries.

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The categories of this paper are: astro-ph
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The categories of this paper are: hep-th
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The categories of this paper are: ao-sci
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The categories of this paper are: supr-con
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The categories of this paper are: q-fin
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The categories of this paper are: q-bio
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The categories of this paper are: hep-ex
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The categories of this paper are: math
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The categories of this paper are: chem-ph
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The categories of this paper are: stat
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The categories of this paper are: nucl-th
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The categories of this paper are: bayes-an
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The categories of this paper are: gr-qc
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The categories of this paper are: math-ph
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The categories of this paper are: eess
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The categories of this paper are: mtrl-th