<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="krause-etal-2024-graph">
    <titleInfo>
        <title>Graph Representations for Machine Translation in Dialogue Settings</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Lea</namePart>
        <namePart type="family">Krause</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Selene</namePart>
        <namePart type="family">Baez Santamaria</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jan-Christoph</namePart>
        <namePart type="family">Kalo</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Ninth Conference on Machine Translation</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Barry</namePart>
            <namePart type="family">Haddow</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Tom</namePart>
            <namePart type="family">Kocmi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Philipp</namePart>
            <namePart type="family">Koehn</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Christof</namePart>
            <namePart type="family">Monz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Miami, Florida, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>In this paper, we present our approach to the WMT24 - Chat Task, addressing the challenge of translating chat conversations.Chat conversations are characterised by their informal, ungrammatical nature and strong reliance on context posing significant challenges for machine translation systems. To address these challenges, we augment large language models with explicit memory mechanisms designed to enhance coherence and consistency across dialogues. Specifically, we employ graph representations to capture and utilise dialogue context, leveraging concept connectivity as a compressed memory. Our approach ranked second place for Dutch and French, and third place for Portuguese and German, based on COMET-22 scores and human evaluation.</abstract>
    <identifier type="citekey">krause-etal-2024-graph</identifier>
    <location>
        <url>https://aclanthology.org/2024.wmt-1.106</url>
    </location>
    <part>
        <date>2024-11</date>
        <extent unit="page">
            <start>1038</start>
            <end>1046</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Graph Representations for Machine Translation in Dialogue Settings
%A Krause, Lea
%A Baez Santamaria, Selene
%A Kalo, Jan-Christoph
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Ninth Conference on Machine Translation
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F krause-etal-2024-graph
%X In this paper, we present our approach to the WMT24 - Chat Task, addressing the challenge of translating chat conversations.Chat conversations are characterised by their informal, ungrammatical nature and strong reliance on context posing significant challenges for machine translation systems. To address these challenges, we augment large language models with explicit memory mechanisms designed to enhance coherence and consistency across dialogues. Specifically, we employ graph representations to capture and utilise dialogue context, leveraging concept connectivity as a compressed memory. Our approach ranked second place for Dutch and French, and third place for Portuguese and German, based on COMET-22 scores and human evaluation.
%U https://aclanthology.org/2024.wmt-1.106
%P 1038-1046

Markdown (Informal)

[Graph Representations for Machine Translation in Dialogue Settings](https://aclanthology.org/2024.wmt-1.106) (Krause et al., WMT 2024)

• Graph Representations for Machine Translation in Dialogue Settings (Krause et al., WMT 2024)

ACL

• Lea Krause, Selene Baez Santamaria, and Jan-Christoph Kalo. 2024. Graph Representations for Machine Translation in Dialogue Settings. In Proceedings of the Ninth Conference on Machine Translation, pages 1038–1046, Miami, Florida, USA. Association for Computational Linguistics.