<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="chen-etal-2021-dialogsum-challenge">
    <titleInfo>
        <title>DialogSum Challenge: Summarizing Real-Life Scenario Dialogues</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Yulong</namePart>
        <namePart type="family">Chen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yang</namePart>
        <namePart type="family">Liu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yue</namePart>
        <namePart type="family">Zhang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 14th International Conference on Natural Language Generation</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Anya</namePart>
            <namePart type="family">Belz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Angela</namePart>
            <namePart type="family">Fan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ehud</namePart>
            <namePart type="family">Reiter</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yaji</namePart>
            <namePart type="family">Sripada</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Aberdeen, Scotland, UK</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We propose a shared task on summarizing real-life scenario dialogues, DialogSum Challenge, to encourage researchers to address challenges in dialogue summarization, which has been less studied by the summarization community. Real-life scenario dialogue summarization has a wide potential application prospect in chat-bot and personal assistant. It contains unique challenges such as special discourse structure, coreference, pragmatics, and social common sense, which require specific representation learning technologies to deal with. We carefully annotate a large-scale dialogue summarization dataset based on multiple public dialogue corpus, opening the door to all kinds of summarization models.</abstract>
    <identifier type="citekey">chen-etal-2021-dialogsum-challenge</identifier>
    <identifier type="doi">10.18653/v1/2021.inlg-1.33</identifier>
    <location>
        <url>https://aclanthology.org/2021.inlg-1.33</url>
    </location>
    <part>
        <date>2021-08</date>
        <extent unit="page">
            <start>308</start>
            <end>313</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T DialogSum Challenge: Summarizing Real-Life Scenario Dialogues
%A Chen, Yulong
%A Liu, Yang
%A Zhang, Yue
%Y Belz, Anya
%Y Fan, Angela
%Y Reiter, Ehud
%Y Sripada, Yaji
%S Proceedings of the 14th International Conference on Natural Language Generation
%D 2021
%8 August
%I Association for Computational Linguistics
%C Aberdeen, Scotland, UK
%F chen-etal-2021-dialogsum-challenge
%X We propose a shared task on summarizing real-life scenario dialogues, DialogSum Challenge, to encourage researchers to address challenges in dialogue summarization, which has been less studied by the summarization community. Real-life scenario dialogue summarization has a wide potential application prospect in chat-bot and personal assistant. It contains unique challenges such as special discourse structure, coreference, pragmatics, and social common sense, which require specific representation learning technologies to deal with. We carefully annotate a large-scale dialogue summarization dataset based on multiple public dialogue corpus, opening the door to all kinds of summarization models.
%R 10.18653/v1/2021.inlg-1.33
%U https://aclanthology.org/2021.inlg-1.33
%U https://doi.org/10.18653/v1/2021.inlg-1.33
%P 308-313

Markdown (Informal)

[DialogSum Challenge: Summarizing Real-Life Scenario Dialogues](https://aclanthology.org/2021.inlg-1.33) (Chen et al., INLG 2021)

• DialogSum Challenge: Summarizing Real-Life Scenario Dialogues (Chen et al., INLG 2021)

ACL

• Yulong Chen, Yang Liu, and Yue Zhang. 2021. DialogSum Challenge: Summarizing Real-Life Scenario Dialogues. In Proceedings of the 14th International Conference on Natural Language Generation, pages 308–313, Aberdeen, Scotland, UK. Association for Computational Linguistics.