Beyond One-Size-Fits-All Summarization: Customizing Summaries for Diverse Users

Beyond One-Size-Fits-All Summarization: Customizing Summaries for Diverse Users | 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 Beyond One-Size-Fits-All Summarization: Customizing Summaries for Diverse Users Mehmet Samet Duran, Tevfik Aytekin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9418915/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In recent years, automatic text summarization has witnessed significantadvancement, particularly with the development of transformer-based models.However, the challenge of controlling the readability level of generated summariesremains an under-explored area, especially for languages with complex linguisticfeatures like Turkish. This gap has the effect of impeding effective communicationand also limits the accessibility of information. Controlling readability of textual datais an important element for creating summaries for different audiences with varyingliteracy and education levels, such as students ranging from primary school to graduatelevel, as well as individuals with diverse educational backgrounds. Summaries thatalign with the needs of specific reader groups can improve comprehension andengagement, ensuring that the intended message is effectively communicated. Furthermore, readability adjustment is essential to expand the usability ofsummarization models in educational and professional domains.Current summarization models often don’t have the mechanisms to adjust thecomplexity of their outputs, resulting in summaries that may be too simplistic or overlycomplex for certain types of reader groups. Developing adaptive models that can tailorcontent to specific readability levels is therefore crucial. To address this problem, we create our own custom dataset and train a model with our custom architecture. Our method ensures that readability levels are effectively controlled while maintaining accuracy and coherence. We rigorously compare our model to a supervised fine-tuned baseline, demonstrating its superiority in generating readability-aware summaries. Automatic text summarization readability large language models artificial intelligence Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-9418915","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624316149,"identity":"b0fb84f5-dcc1-4ed8-973b-fe738bd53d4a","order_by":0,"name":"Mehmet Samet Duran","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYNACNhDBfPzDBxCbnRgdB8Ba2NIYZ4AoZuK18Jgx84BtI6Bavv104uMPZYfz+Wf3mD22+bVNno+ZgfHDxxzcWgzO5G42OHDusOWMO8fKjXP7bhu2MTMwS87chkcLQ+42iYNthw0YbiRvkM7tuc0I1MLGzItHi3z/2+0/QFrkbyQYSFv23LYnqIXhRu42BpAWgxspZtIMP24nEtRicOPtZokz59INDG+kJRv2NtxObmNmbMbrF/n+3I0fKsqsDeRuJB988OPPbdv57c0HP3zE5zAUwNgGJhuIVQ8Cf0hRPApGwSgYBSMFAAB58Fbl9Gj31wAAAABJRU5ErkJggg==","orcid":"","institution":"Bahçeşehir University","correspondingAuthor":true,"prefix":"","firstName":"Mehmet","middleName":"Samet","lastName":"Duran","suffix":""},{"id":624316150,"identity":"bbfebcba-4044-4389-b3ee-4ed64b9cf7ec","order_by":1,"name":"Tevfik Aytekin","email":"","orcid":"","institution":"Bahçeşehir University","correspondingAuthor":false,"prefix":"","firstName":"Tevfik","middleName":"","lastName":"Aytekin","suffix":""}],"badges":[],"createdAt":"2026-04-14 18:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9418915/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9418915/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107424463,"identity":"f4b2de05-a788-46c3-bde3-84f545acb447","added_by":"auto","created_at":"2026-04-21 10:57:39","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1897458,"visible":true,"origin":"","legend":"","description":"","filename":"kaisyod.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9418915/v1_covered_78b4a7f7-955c-442f-a377-07cebf5060cd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beyond One-Size-Fits-All Summarization: Customizing Summaries for Diverse Users","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Automatic text summarization, readability, large language models, artificial intelligence","lastPublishedDoi":"10.21203/rs.3.rs-9418915/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9418915/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn recent years, automatic text summarization has witnessed significantadvancement, particularly with the development of transformer-based models.However, the challenge of controlling the readability level of generated summariesremains an under-explored area, especially for languages with complex linguisticfeatures like Turkish. 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