<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="sauvage-etal-2024-structure">
    <titleInfo>
        <title>Does the structure of textual content have an impact on language models for automatic summarization?</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Eve</namePart>
        <namePart type="family">Sauvage</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sabrina</namePart>
        <namePart type="family">Campano</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Lydia</namePart>
        <namePart type="family">Ouali</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Cyril</namePart>
        <namePart type="family">Grouin</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Xiyan</namePart>
            <namePart type="family">Fu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Eve</namePart>
            <namePart type="family">Fleisig</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Bangkok, Thailand</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>The processing of long sequences with models remains a subject in its own right, including automatic summary, despite recent improvements. In this work, we present experiments on the automatic summarization of scientific articles using BART models, taking into account textual information coming from distinct passages from the long texts to be summarized. We demonstrate that taking into account document structure improves the performance of state-of-the-art models and approaches the performance of LongFormer on English.</abstract>
    <identifier type="citekey">sauvage-etal-2024-structure</identifier>
    <identifier type="doi">10.18653/v1/2024.acl-srw.25</identifier>
    <location>
        <url>https://aclanthology.org/2024.acl-srw.25</url>
    </location>
    <part>
        <date>2024-08</date>
        <extent unit="page">
            <start>186</start>
            <end>191</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Does the structure of textual content have an impact on language models for automatic summarization?
%A Sauvage, Eve
%A Campano, Sabrina
%A Ouali, Lydia
%A Grouin, Cyril
%Y Fu, Xiyan
%Y Fleisig, Eve
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F sauvage-etal-2024-structure
%X The processing of long sequences with models remains a subject in its own right, including automatic summary, despite recent improvements. In this work, we present experiments on the automatic summarization of scientific articles using BART models, taking into account textual information coming from distinct passages from the long texts to be summarized. We demonstrate that taking into account document structure improves the performance of state-of-the-art models and approaches the performance of LongFormer on English.
%R 10.18653/v1/2024.acl-srw.25
%U https://aclanthology.org/2024.acl-srw.25
%U https://doi.org/10.18653/v1/2024.acl-srw.25
%P 186-191

Markdown (Informal)

[Does the structure of textual content have an impact on language models for automatic summarization?](https://aclanthology.org/2024.acl-srw.25) (Sauvage et al., ACL 2024)

• Does the structure of textual content have an impact on language models for automatic summarization? (Sauvage et al., ACL 2024)

ACL

• Eve Sauvage, Sabrina Campano, Lydia Ouali, and Cyril Grouin. 2024. Does the structure of textual content have an impact on language models for automatic summarization?. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 186–191, Bangkok, Thailand. Association for Computational Linguistics.