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        <title>Paper Abstract Writing through Editing Mechanism</title>
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    <name type="personal">
        <namePart type="given">Qingyun</namePart>
        <namePart type="family">Wang</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Zhihao</namePart>
        <namePart type="family">Zhou</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Lifu</namePart>
        <namePart type="family">Huang</namePart>
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    <name type="personal">
        <namePart type="given">Spencer</namePart>
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    <name type="personal">
        <namePart type="given">Boliang</namePart>
        <namePart type="family">Zhang</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Heng</namePart>
        <namePart type="family">Ji</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Kevin</namePart>
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        <dateIssued>2018-07</dateIssued>
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            <title>Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</title>
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            <namePart type="given">Iryna</namePart>
            <namePart type="family">Gurevych</namePart>
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        <name type="personal">
            <namePart type="given">Yusuke</namePart>
            <namePart type="family">Miyao</namePart>
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            <publisher>Association for Computational Linguistics</publisher>
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    <abstract>We present a paper abstract writing system based on an attentive neural sequence-to-sequence model that can take a title as input and automatically generate an abstract. We design a novel Writing-editing Network that can attend to both the title and the previously generated abstract drafts and then iteratively revise and polish the abstract. With two series of Turing tests, where the human judges are asked to distinguish the system-generated abstracts from human-written ones, our system passes Turing tests by junior domain experts at a rate up to 30% and by non-expert at a rate up to 80%.</abstract>
    <identifier type="citekey">wang-etal-2018-paper</identifier>
    <identifier type="doi">10.18653/v1/P18-2042</identifier>
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        <url>https://aclanthology.org/P18-2042</url>
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    <part>
        <date>2018-07</date>
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            <start>260</start>
            <end>265</end>
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%0 Conference Proceedings
%T Paper Abstract Writing through Editing Mechanism
%A Wang, Qingyun
%A Zhou, Zhihao
%A Huang, Lifu
%A Whitehead, Spencer
%A Zhang, Boliang
%A Ji, Heng
%A Knight, Kevin
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F wang-etal-2018-paper
%X We present a paper abstract writing system based on an attentive neural sequence-to-sequence model that can take a title as input and automatically generate an abstract. We design a novel Writing-editing Network that can attend to both the title and the previously generated abstract drafts and then iteratively revise and polish the abstract. With two series of Turing tests, where the human judges are asked to distinguish the system-generated abstracts from human-written ones, our system passes Turing tests by junior domain experts at a rate up to 30% and by non-expert at a rate up to 80%.
%R 10.18653/v1/P18-2042
%U https://aclanthology.org/P18-2042
%U https://doi.org/10.18653/v1/P18-2042
%P 260-265

Markdown (Informal)

[Paper Abstract Writing through Editing Mechanism](https://aclanthology.org/P18-2042) (Wang et al., ACL 2018)

• Paper Abstract Writing through Editing Mechanism (Wang et al., ACL 2018)

ACL

• Qingyun Wang, Zhihao Zhou, Lifu Huang, Spencer Whitehead, Boliang Zhang, Heng Ji, and Kevin Knight. 2018. Paper Abstract Writing through Editing Mechanism. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 260–265, Melbourne, Australia. Association for Computational Linguistics.