<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="trokhymovych-etal-2025-graph">
    <titleInfo>
        <title>Graph-Linguistic Fusion: Using Language Models for Wikidata Vandalism Detection</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Mykola</namePart>
        <namePart type="family">Trokhymovych</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Lydia</namePart>
        <namePart type="family">Pintscher</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ricardo</namePart>
        <namePart type="family">Baeza-Yates</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Diego</namePart>
        <namePart type="family">Sáez Trumper</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2025-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Georg</namePart>
            <namePart type="family">Rehm</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yunyao</namePart>
            <namePart type="family">Li</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Vienna, Austria</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-288-6</identifier>
    </relatedItem>
    <abstract>We introduce a next-generation vandalism detection system for Wikidata, one of the largest open-source structured knowledge bases on the Web. Wikidata is highly complex: its items incorporate an ever-expanding universe of factual triples and multilingual texts. While edits can alter both structured and textual content, our approach converts all edits into a single space using a method we call Graph2Text. This allows for evaluating all content changes for potential vandalism using a single multilingual language model. This unified approach improves coverage and simplifies maintenance. Experiments demonstrate that our solution outperforms the current production system. Additionally, we are releasing the code under an open license along with a large dataset of various human-generated knowledge alterations, enabling further research.</abstract>
    <identifier type="citekey">trokhymovych-etal-2025-graph</identifier>
    <identifier type="doi">10.18653/v1/2025.acl-industry.21</identifier>
    <location>
        <url>https://aclanthology.org/2025.acl-industry.21/</url>
    </location>
    <part>
        <date>2025-07</date>
        <extent unit="page">
            <start>284</start>
            <end>294</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Graph-Linguistic Fusion: Using Language Models for Wikidata Vandalism Detection
%A Trokhymovych, Mykola
%A Pintscher, Lydia
%A Baeza-Yates, Ricardo
%A Sáez Trumper, Diego
%Y Rehm, Georg
%Y Li, Yunyao
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-288-6
%F trokhymovych-etal-2025-graph
%X We introduce a next-generation vandalism detection system for Wikidata, one of the largest open-source structured knowledge bases on the Web. Wikidata is highly complex: its items incorporate an ever-expanding universe of factual triples and multilingual texts. While edits can alter both structured and textual content, our approach converts all edits into a single space using a method we call Graph2Text. This allows for evaluating all content changes for potential vandalism using a single multilingual language model. This unified approach improves coverage and simplifies maintenance. Experiments demonstrate that our solution outperforms the current production system. Additionally, we are releasing the code under an open license along with a large dataset of various human-generated knowledge alterations, enabling further research.
%R 10.18653/v1/2025.acl-industry.21
%U https://aclanthology.org/2025.acl-industry.21/
%U https://doi.org/10.18653/v1/2025.acl-industry.21
%P 284-294

Markdown (Informal)

[Graph-Linguistic Fusion: Using Language Models for Wikidata Vandalism Detection](https://aclanthology.org/2025.acl-industry.21/) (Trokhymovych et al., ACL 2025)

• Graph-Linguistic Fusion: Using Language Models for Wikidata Vandalism Detection (Trokhymovych et al., ACL 2025)

ACL

• Mykola Trokhymovych, Lydia Pintscher, Ricardo Baeza-Yates, and Diego Sáez Trumper. 2025. Graph-Linguistic Fusion: Using Language Models for Wikidata Vandalism Detection. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track), pages 284–294, Vienna, Austria. Association for Computational Linguistics.