融合知识图谱的Transformer课程理论智能图像生成方法研究

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中图分类号：TP391 文献标识码：A

文章编号：1006-8228（2025）10-17-08

Research on a Transformer-based Intelligent Image Generation Method using Knowledge Graph for Curriculum Theory

WangMin，Bai Changsheng

（Shanxi InstituteofScienceand Technology，Jincheng，Shanxi O48o11，China）

Abstract：Toaddressthechallngesofcomplexlogicinomputercurriulumthoryandtheinefficincyoftraditioalvisualiaion tolsthisstudyinnovativelyintegratesTransfomerandknowledgegraphtechnologies，andproposesaTransformer-basedimage generationmodelbasedoncros-modalinformationintegrationandknowledgegraph-fusedThemodelintegratestextualsemantic informatioandthestructuralinformationoftheknowledgegraphstroughcross-modalencoding，anddesignsalogicalcostraint injectionmechanismtoguidethegenerationprocesstfollowcorectknowledgelogic.LRAparameterfine-tuningisintroducedto solvetheproblemofsparsetrainingdataineducationalscenarios.Theexperimentalresultsdemonstratethatcomparedtothe general-purpose Stable Diffusion XL model， the proposed approach achieves improvements of 13.2% inknowledge alignment accuracy and 17.2% inrelationalaccuracy.This ofersan effective technical pathwayfor visualizing course theoriesunder smalsampleand high-logicality constraints.

Keywords：Transformer;Knowledge Graph;LoRA;Stable Diffusion XI

0引言

在教育信息化2.0时代，有效的知识传递已成为教育改革的关键目标。（剩余12553字）