{"paper_id":"4a1716ff-c126-43c8-948e-fa4e898cfbb4","body_text":"Interpreting DETR with Respect to Object Queries | 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 Interpreting DETR with Respect to Object Queries Morteza Shahrabi Farahani, Mohammad Javad Mirshekari Haghighi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5659752/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, understanding the decision-making processes of neural network models has become increasingly important. This paper is focusing on this concern and addresses this issue on DETR model which is an object detection framework based on transformers. We explore ways to improve the interpretability and efficiency of this model by proposing and applying new methods for representing this model. A key focus of this research is on object queries specifically analyzing their behavior during the model's validation process. We identify and remove less active object queries from the model, subsequently, measuring the impact on the training time and also the model accuracy. By eliminating 10% of these inactive object queries, we reduce validation time by 3.3% and lower the model’s required FLOPS by 36.25 G. The GitHub repository for this project is available at https://github.com/morteza-shahrabi-farahani/Interpreted-DETR-model object detection DETR model Explainability Interpredibility object query explainable AI 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5659752\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":391523458,\"identity\":\"a4106851-27ee-44a2-9236-d95d878b0501\",\"order_by\":0,\"name\":\"Morteza Shahrabi Farahani\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYHACNgbGBgYGA2bmAwwP4FwwgDNwaWFLYEiAcxOI0cLAYwBRCAYJOBQDgW4D+7MHP3fckzdn5/n4IbFtWx4fA3Ob5M8fDPL8DcxtH7BoMTvAY27Ye6bYcGcz72aJxLbbxUBL26R5EhgMZxxgbJ6BXQubBG9bAuOGw7wbQFoS20BagA5j3MDA2IzNYWYH2J9J/m1LsN9wmOfxD5gWyR8JDPa4tTCYSQNtSQRqYYPbIgF0WCJuLTxm0rJtCck7m9nMLBLOAbUwMzZb86RJJM84jMdhb9sSbLfzH35840PZ7cT57e0Pb/6wsbHtb29/jDWU5R+gizCDSQkYYxSMglEwCkYBGQAAmKNfY2R+/agAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Iran University of Science and Technology\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Morteza\",\"middleName\":\"Shahrabi\",\"lastName\":\"Farahani\",\"suffix\":\"\"},{\"id\":391523459,\"identity\":\"4f4d4fb9-0004-4bf8-b70d-93df77fc0ccb\",\"order_by\":1,\"name\":\"Mohammad Javad Mirshekari Haghighi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Iran University of Science and Technology\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohammad\",\"middleName\":\"Javad Mirshekari\",\"lastName\":\"Haghighi\",\"suffix\":\"\"},{\"id\":391523460,\"identity\":\"61b10f4e-61be-4675-947b-675a89a8ea24\",\"order_by\":2,\"name\":\"Mohammad Reza Mohammadi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Iran University of Science and Technology\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohammad\",\"middleName\":\"Reza\",\"lastName\":\"Mohammadi\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-12-17 08:23:37\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5659752/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5659752/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":75113467,\"identity\":\"8471109c-3917-48ce-ae05-53e4da0e8a5a\",\"added_by\":\"auto\",\"created_at\":\"2025-01-30 15:47:04\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1025444,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"InterpretingDETRwithrespecttoobjectqueries.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5659752/v1_covered_b9a9267d-2017-400c-af2a-634d74d2d812.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Interpreting DETR with Respect to Object Queries\",\"fulltext\":[],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":false,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"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\":\"info@researchsquare.com\",\"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\":\"object detection, DETR model, Explainability, Interpredibility, object query, explainable AI\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5659752/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5659752/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eIn recent years, understanding the decision-making processes of neural network models has become increasingly important. 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