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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">GLCS</journal-id><journal-title-group><journal-title>Global Language and Cultural Studies</journal-title></journal-title-group><issn>3083-3043</issn><eissn>3083-3035</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/GLCS.v1i1.15839</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>English Translation of Ancient Chinese Scientific Classics in the AIPE Era: Efficacy, Boundaries, and Pathways —An Empirical Study Based on the Translation Review of Mengxi Bitan</title><url>https://artdesignp.com/journal/GLCS/1/1/10.26689/GLCS.v1i1.15839</url><author>WangZipeng,LiuShiying</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>1</volume><issue>1</issue><history><date date-type="pub"><published-time>2026-02-10</published-time></date></history><abstract>Current research on Artificial Intelligence Post-Editing (AIPE) remains largely theoretical, lacking sufficient empirical, case-specific, and quantitative analysis. This study investigates the efficacy, boundaries, and developmental pathways of AIPE in translating ancient Chinese scientific classics, using the English translation of Mengxi Bitan&amp;nbsp;(Brush Talks from Dream Brook) by Shen Kuo (1031-1095) as a case study and integrating quantitative and qualitative methods. The findings reveal that, despite multiple rounds of prompt engineering and Few-Shot Learning (FSL) training, AI continues to exhibit significant limitations: it is prone to factual and contextual hallucinations, lacks empathetic perception, and struggles to capture the emotional and cultural nuances of the source text or adapt to target readers&amp;rsquo; cognitive gaps. The study concludes that AI currently serves only as an auxiliary tool and is not yet capable of functioning independently as a translation reviewer in the short term. This research aims to fill the empirical gap in AIPE-assisted translation of scientific classics, underscores the necessity of building a human-AI collaborative model, and proposes strategies for enhancing the competence of human reviewers and optimizing AI performance to achieve synchronous improvements in both translation efficiency and quality.</abstract><keywords>AIPE,English translation of scientific classics,Mengxi Bitan,hallucination,empathy</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]Wang H, Zhu H, 2025,&amp;nbsp;Artificial Intelligence Translation and Post-editing. 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