<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="cao-etal-2024-bridging">
    <titleInfo>
        <title>Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Yong</namePart>
        <namePart type="family">Cao</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Min</namePart>
        <namePart type="family">Chen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Daniel</namePart>
        <namePart type="family">Hershcovich</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-03</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Findings of the Association for Computational Linguistics: EACL 2024</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Yvette</namePart>
            <namePart type="family">Graham</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Matthew</namePart>
            <namePart type="family">Purver</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">St. Julian’s, Malta</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory. It’s clear that various sociocultural aspects—from communication styles and beliefs to shared metaphors and knowledge—profoundly impact these interactions. To delve deeper into this dynamic, we introduce cuDialog, a first-of-its-kind benchmark for dialogue generation with a cultural lens. We also develop baseline models capable of extracting cultural attributes from dialogue exchanges, with the goal of enhancing the predictive accuracy and quality of dialogue agents. To effectively co-learn cultural understanding and multi-turn dialogue predictions, we propose to incorporate cultural dimensions with dialogue encoding features. Our experimental findings highlight that incorporating cultural value surveys boosts alignment with references and cultural markers, demonstrating its considerable influence on personalization and dialogue quality. To facilitate further exploration in this exciting domain, we publish our benchmark publicly accessible at https://github.com/yongcaoplus/cuDialog.</abstract>
    <identifier type="citekey">cao-etal-2024-bridging</identifier>
    <location>
        <url>https://aclanthology.org/2024.findings-eacl.63</url>
    </location>
    <part>
        <date>2024-03</date>
        <extent unit="page">
            <start>929</start>
            <end>945</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys
%A Cao, Yong
%A Chen, Min
%A Hershcovich, Daniel
%Y Graham, Yvette
%Y Purver, Matthew
%S Findings of the Association for Computational Linguistics: EACL 2024
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julian’s, Malta
%F cao-etal-2024-bridging
%X The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory. It’s clear that various sociocultural aspects—from communication styles and beliefs to shared metaphors and knowledge—profoundly impact these interactions. To delve deeper into this dynamic, we introduce cuDialog, a first-of-its-kind benchmark for dialogue generation with a cultural lens. We also develop baseline models capable of extracting cultural attributes from dialogue exchanges, with the goal of enhancing the predictive accuracy and quality of dialogue agents. To effectively co-learn cultural understanding and multi-turn dialogue predictions, we propose to incorporate cultural dimensions with dialogue encoding features. Our experimental findings highlight that incorporating cultural value surveys boosts alignment with references and cultural markers, demonstrating its considerable influence on personalization and dialogue quality. To facilitate further exploration in this exciting domain, we publish our benchmark publicly accessible at https://github.com/yongcaoplus/cuDialog.
%U https://aclanthology.org/2024.findings-eacl.63
%P 929-945

Markdown (Informal)

[Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys](https://aclanthology.org/2024.findings-eacl.63) (Cao et al., Findings 2024)

• Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys (Cao et al., Findings 2024)

ACL

• Yong Cao, Min Chen, and Daniel Hershcovich. 2024. Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys. In Findings of the Association for Computational Linguistics: EACL 2024, pages 929–945, St. Julian’s, Malta. Association for Computational Linguistics.