Research on Intelligent Content Generation and Adaptive Presentation in Virtual Simulation Scenarios

Research on Intelligent Content Generation and Adaptive Presentation in Virtual Simulation Scenarios | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Research on Intelligent Content Generation and Adaptive Presentation in Virtual Simulation Scenarios Xuezhi Fan, Jie Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8639787/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Virtual simulation technologies have become indispensable in education, medical training, psychological therapy, and industrial applications. However, traditional virtual systems rely heavily on static pre-designed content and simple rule-based adaptations, resulting in limited personalization, suboptimal immersion, and increased cybersickness. This paper proposes the Adaptive Generative Virtual Ecosystem (AGVE), a novel closed-loop framework that integrates intelligent content generation with real-time adaptive presentation. AGVE comprises three synergistic layers: a perception layer using a Conditional Multimodal Variational Autoencoder for uncertainty-aware user state modeling, a generation layer employing a User-Conditioned Latent Diffusion Model for semantically coherent 3D content creation, and an adaptation layer based on Multi-Objective Actor-Critic with Online Bayesian Weight Adaptation for dynamic, preference-aware presentation optimization. Extensive experiments in educational virtual chemistry laboratories and therapeutic spider phobia exposure scenarios demonstrate significant improvements: 41.7% relative gain in immersion, 28.3% increase in learning outcomes, 39.9% reduction in cybersickness, and up to 47.8% better task performance. Ablation studies and user feedback further validate the necessity and effectiveness of the integrated architecture. This work advances toward truly intelligent, human-centered virtual ecosystems. Virtual simulation generative AI adaptive presentation user-conditioned diffusion multimodal perception reinforcement learning extended reality Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Mar, 2026 Reviews received at journal 28 Feb, 2026 Reviews received at journal 21 Feb, 2026 Reviewers agreed at journal 19 Feb, 2026 Reviews received at journal 18 Feb, 2026 Reviewers agreed at journal 15 Feb, 2026 Reviewers agreed at journal 15 Feb, 2026 Reviewers agreed at journal 14 Feb, 2026 Reviewers agreed at journal 13 Feb, 2026 Reviewers invited by journal 12 Feb, 2026 Editor invited by journal 01 Feb, 2026 Editor assigned by journal 29 Jan, 2026 Submission checks completed at journal 25 Jan, 2026 First submitted to journal 25 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8639787","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":591746009,"identity":"0f4cd59e-8ee5-48d0-9049-094c8c59c5e9","order_by":0,"name":"Xuezhi Fan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xuezhi","middleName":"","lastName":"Fan","suffix":""},{"id":591746011,"identity":"17345087-353a-4d6e-9259-3d69345d2ccf","order_by":1,"name":"Jie Zhang","email":"data:image/png;base64,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","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Jie","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-01-19 13:02:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8639787/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8639787/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102868002,"identity":"ea649297-d6b5-4a71-91a1-ee04ac6c2865","added_by":"auto","created_at":"2026-02-17 17:10:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":785372,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8639787/v1_covered_01ec0997-9527-49f5-9efa-f4306cf4cde1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on Intelligent Content Generation and Adaptive Presentation in Virtual Simulation Scenarios","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-artificial-intelligence","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diai","sideBox":"Learn more about [Discover Artificial Intelligence](https://www.springer.com/44163)","snPcode":"","submissionUrl":"","title":"Discover Artificial Intelligence","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Virtual simulation, generative AI, adaptive presentation, user-conditioned diffusion, multimodal perception, reinforcement learning, extended reality","lastPublishedDoi":"10.21203/rs.3.rs-8639787/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8639787/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVirtual simulation technologies have become indispensable in education, medical training, psychological therapy, and industrial applications. 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