<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="chen-etal-2022-dialogsum">
    <titleInfo>
        <title>DialogSum Challenge: Results of the Dialogue Summarization Shared Task</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">Naihao</namePart>
        <namePart type="family">Deng</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>2022-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Samira</namePart>
            <namePart type="family">Shaikh</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Thiago</namePart>
            <namePart type="family">Ferreira</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Amanda</namePart>
            <namePart type="family">Stent</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Waterville, Maine, USA and virtual meeting</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We report the results of DialogSum Challenge, the shared task on summarizing real-life sce- nario dialogues at INLG 2022. Four teams participate in this shared task and three submit their system reports, exploring different meth- ods to improve the performance of dialogue summarization. Although there is a great im- provement over the baseline models regarding automatic evaluation metrics, such as ROUGE scores, we find that there is a salient gap be- tween model generated outputs and human an- notated summaries by human evaluation from multiple aspects. These findings demonstrate the difficulty of dialogue summarization and suggest that more fine-grained evaluatuion met- rics are in need.</abstract>
    <identifier type="citekey">chen-etal-2022-dialogsum</identifier>
    <location>
        <url>https://aclanthology.org/2022.inlg-genchal.14</url>
    </location>
    <part>
        <date>2022-07</date>
        <extent unit="page">
            <start>94</start>
            <end>103</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T DialogSum Challenge: Results of the Dialogue Summarization Shared Task
%A Chen, Yulong
%A Deng, Naihao
%A Liu, Yang
%A Zhang, Yue
%Y Shaikh, Samira
%Y Ferreira, Thiago
%Y Stent, Amanda
%S Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges
%D 2022
%8 July
%I Association for Computational Linguistics
%C Waterville, Maine, USA and virtual meeting
%F chen-etal-2022-dialogsum
%X We report the results of DialogSum Challenge, the shared task on summarizing real-life sce- nario dialogues at INLG 2022. Four teams participate in this shared task and three submit their system reports, exploring different meth- ods to improve the performance of dialogue summarization. Although there is a great im- provement over the baseline models regarding automatic evaluation metrics, such as ROUGE scores, we find that there is a salient gap be- tween model generated outputs and human an- notated summaries by human evaluation from multiple aspects. These findings demonstrate the difficulty of dialogue summarization and suggest that more fine-grained evaluatuion met- rics are in need.
%U https://aclanthology.org/2022.inlg-genchal.14
%P 94-103

Markdown (Informal)

[DialogSum Challenge: Results of the Dialogue Summarization Shared Task](https://aclanthology.org/2022.inlg-genchal.14) (Chen et al., INLG 2022)

• DialogSum Challenge: Results of the Dialogue Summarization Shared Task (Chen et al., INLG 2022)

ACL

• Yulong Chen, Naihao Deng, Yang Liu, and Yue Zhang. 2022. DialogSum Challenge: Results of the Dialogue Summarization Shared Task. In Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges, pages 94–103, Waterville, Maine, USA and virtual meeting. Association for Computational Linguistics.