<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="hitomi-etal-2017-proofread">
    <titleInfo>
        <title>Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Yuta</namePart>
        <namePart type="family">Hitomi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Hideaki</namePart>
        <namePart type="family">Tamori</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Naoaki</namePart>
        <namePart type="family">Okazaki</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kentaro</namePart>
        <namePart type="family">Inui</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2017-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Greg</namePart>
            <namePart type="family">Kondrak</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Taro</namePart>
            <namePart type="family">Watanabe</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Asian Federation of Natural Language Processing</publisher>
            <place>
                <placeTerm type="text">Taipei, Taiwan</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper explores the idea of robot editors, automated proofreaders that enable journalists to improve the quality of their articles. We propose a novel neural model of multi-task learning that both generates proofread sentences and predicts the editing operations required to rewrite the source sentences and create the proofread ones. The model is trained using logs of the revisions made professional editors revising draft newspaper articles written by journalists. Experiments demonstrate the effectiveness of our multi-task learning approach and the potential value of using revision logs for this task.</abstract>
    <identifier type="citekey">hitomi-etal-2017-proofread</identifier>
    <location>
        <url>https://aclanthology.org/I17-2074</url>
    </location>
    <part>
        <date>2017-11</date>
        <extent unit="page">
            <start>436</start>
            <end>441</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction
%A Hitomi, Yuta
%A Tamori, Hideaki
%A Okazaki, Naoaki
%A Inui, Kentaro
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F hitomi-etal-2017-proofread
%X This paper explores the idea of robot editors, automated proofreaders that enable journalists to improve the quality of their articles. We propose a novel neural model of multi-task learning that both generates proofread sentences and predicts the editing operations required to rewrite the source sentences and create the proofread ones. The model is trained using logs of the revisions made professional editors revising draft newspaper articles written by journalists. Experiments demonstrate the effectiveness of our multi-task learning approach and the potential value of using revision logs for this task.
%U https://aclanthology.org/I17-2074
%P 436-441

Markdown (Informal)

[Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction](https://aclanthology.org/I17-2074) (Hitomi et al., IJCNLP 2017)

• Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction (Hitomi et al., IJCNLP 2017)

ACL

• Yuta Hitomi, Hideaki Tamori, Naoaki Okazaki, and Kentaro Inui. 2017. Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 436–441, Taipei, Taiwan. Asian Federation of Natural Language Processing.