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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JCER</journal-id><journal-title-group><journal-title>Journal of Contemporary Educational Research</journal-title></journal-title-group><issn>2208-8466</issn><eissn>2208-8474</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jcer.v9i4.10369</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>A Study on the Performance of Large Language Models in Translating the Texts of Red Culture into English</title><url>https://artdesignp.com/journal/JCER/9/4/10.26689/jcer.v9i4.10369</url><author>LiYiming,HuangYuanpeng</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>4</issue><history><date date-type="pub"><published-time>2025-04-29</published-time></date></history><abstract>This paper takes Chinese red culture resources as its research subject and focuses on evaluating the Chinese-English translation quality of three major AI platforms: ChatGPT-4.0, ERNIE Bot, and DeepSeek. 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