<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="jeong-kang-2026-herit">
    <titleInfo>
        <title>HERIT: Enabling Global Access to Hanja-to-English Historical Translation by Mitigating Temporal Bias</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Dayeon</namePart>
        <namePart type="family">Jeong</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kyeongpil</namePart>
        <namePart type="family">Kang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2026-10</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Findings of the Association for Computational Linguistics: EMNLP 2026</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Hung-Yi</namePart>
            <namePart type="family">Lee</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sunipa</namePart>
            <namePart type="family">Dev</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Jessy</namePart>
            <namePart type="family">Li</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Desmond</namePart>
            <namePart type="family">Elliott</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Budapest, Hungary</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-462-0</identifier>
    </relatedItem>
    <abstract>Historical archives are invaluable for multidisciplinary research but remain inaccessible globally due to severe language barriers. While manual translation is prohibitively expensive and time-consuming, simply applying existing machine translation models is inadequate due to unique linguistic nuances and the temporal bias inherent in scarce human-labeled corpora. To address these challenges, we propose HERIT, a systematic domain-adaptation pipeline that leverages retrieval-augmented generation (RAG) to generate high-quality pseudo-labeled data from abundant Hanja-Korean corpora. This approach substantially expands the training dataset, mitigating both data scarcity and temporal overfitting across different historical periods. Extensive automated and human evaluations demonstrate that HERIT consistently outperforms baselines. Finally, we translate previously untranslated portions of the archives using our model, thereby enabling global access to these resources for researchers.</abstract>
    <identifier type="citekey">jeong-kang-2026-herit</identifier>
    <location>
        <url>https://aclanthology.org/2026.findings-emnlp.2326/</url>
    </location>
    <part>
        <date>2026-10</date>
        <extent unit="page">
            <start>49937</start>
            <end>49953</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T HERIT: Enabling Global Access to Hanja-to-English Historical Translation by Mitigating Temporal Bias
%A Jeong, Dayeon
%A Kang, Kyeongpil
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Findings of the Association for Computational Linguistics: EMNLP 2026
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-462-0
%F jeong-kang-2026-herit
%X Historical archives are invaluable for multidisciplinary research but remain inaccessible globally due to severe language barriers. While manual translation is prohibitively expensive and time-consuming, simply applying existing machine translation models is inadequate due to unique linguistic nuances and the temporal bias inherent in scarce human-labeled corpora. To address these challenges, we propose HERIT, a systematic domain-adaptation pipeline that leverages retrieval-augmented generation (RAG) to generate high-quality pseudo-labeled data from abundant Hanja-Korean corpora. This approach substantially expands the training dataset, mitigating both data scarcity and temporal overfitting across different historical periods. Extensive automated and human evaluations demonstrate that HERIT consistently outperforms baselines. Finally, we translate previously untranslated portions of the archives using our model, thereby enabling global access to these resources for researchers.
%U https://aclanthology.org/2026.findings-emnlp.2326/
%P 49937-49953

Markdown (Informal)

[HERIT: Enabling Global Access to Hanja-to-English Historical Translation by Mitigating Temporal Bias](https://aclanthology.org/2026.findings-emnlp.2326/) (Jeong & Kang, Findings 2026)

• HERIT: Enabling Global Access to Hanja-to-English Historical Translation by Mitigating Temporal Bias (Jeong & Kang, Findings 2026)

ACL

• Dayeon Jeong and Kyeongpil Kang. 2026. HERIT: Enabling Global Access to Hanja-to-English Historical Translation by Mitigating Temporal Bias. In Findings of the Association for Computational Linguistics: EMNLP 2026, pages 49937–49953, Budapest, Hungary. Association for Computational Linguistics.