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Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models

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Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models
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Researchers have released a paper on YOLO26, a new unified real-time end-to-end vision model. The submission is hosted on arXiv and includes links to associated code and academic citation tools.

Why it matters

YOLO models are industry standards for real-time object detection, and updates to this architecture significantly impact computer vision applications in robotics and autonomous systems.

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Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Glenn Jocher [ view email ] [v1] Tue, 2 Jun 2026 15:01:13 UTC (8,589 KB) Full-text links: Access Paper: View a PDF of the paper titled Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models, by Glenn Jocher and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.CV < prev | next > new | recent | 2026-06 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

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