{"paper_id":"37f40deb-0159-4df1-b4a2-d4d43dc8d004","body_text":"An Application Unlocking Image Aesthetic EvaluationExpertise | 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 Article An Application Unlocking Image Aesthetic EvaluationExpertise Yi Li, Lun Zhang, Ya Juan Sun, Qing Dong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7726376/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The training period for developing aesthetic perception among novice photographers is typically limited to 3-6 weeks. Suchshort-term training is likely to create a significant gap between instruction and professional practice. To address this issue, weintroduce IAAS-an interpretable image aesthetics assessment system that leverages ResNet101 and Grad-CAM to processimages in a module-based manner and annotate heatmap-based attributes. This approach enables the quantification ofaesthetics through the extraction of image features. Using Kolmogorov-Arnold Networks (KAN), the system integrates attribute-level aesthetic scores into an overall aesthetic evaluation, while a Multi-modal Large Language Model (MLLM) provides naturallanguage instructional narratives. Experiments involving 150 practitioners demonstrate the effectiveness of IAAS, with anaccuracy rate of 58.24%. The findings indicate that the system can guide learners in understanding aesthetic reasoning andhelp narrow the skill gap for novice photographers. Physical sciences/Engineering Physical sciences/Mathematics and computing Multimodel Explainable AI Knowledge Distillation Aesthetic Computing Human-AI Collaboration Vocational Skill Transfer Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Dec, 2025 Reviews received at journal 15 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviews received at journal 25 Oct, 2025 Reviewers agreed at journal 19 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviewers invited by journal 14 Oct, 2025 Editor assigned by journal 14 Oct, 2025 Editor invited by journal 14 Oct, 2025 Submission checks completed at journal 06 Oct, 2025 First submitted to journal 06 Oct, 2025 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. 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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-7726376\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":531926052,\"identity\":\"ae3f3df4-26a0-4eab-ac07-0ba651076efd\",\"order_by\":0,\"name\":\"Yi 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