ECN AI Baseline Index 2024: Stable Accessible AI Performance Across Difficulty Shifts

ECN AI Baseline Index 2024: Stable Accessible AI Performance Across Difficulty Shifts | 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 ECN AI Baseline Index 2024: Stable Accessible AI Performance Across Difficulty Shifts Zoltán Kátai, David Iclanzan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8976478/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract We present the 2024 edition of the ECN AI Baseline Index (EAII), an accessible benchmark evaluating large language models in competitive programming under contest conditions. The 2024 Sapientia–ECN universities division included 11 teams and 16 university-track problems (a 17th, Problem K, was reserved for high-school teams) and introduced a judging platform restricted to C/C++/Pascal. Using a simple C++ prompting protocol with limited feedback rounds, the AI fully solved 13 of 16 problems (81.25%), partially solved two, and failed on one interactive task. Student teams achieved a median of nine and a maximum of twelve solved problems. The resulting 2024 EAII value is 125%. We provide per-problem and team-level analyses, along with figures summarizing score distributions, problem-specific solve rates, and year-over-year comparisons with 2023. Despite a markedly easier contest and a shift in the AI language channel (C++ versus Python), EAII remains stable relative to 2023, supporting the robustness of the normalization procedure. Interpretation is reserved for the Discussion ; this paper focuses on methodology, descriptive analyses, and numerical results. Full Text Additional Declarations Competing interest reported. Editorial Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Apr, 2026 Reviews received at journal 19 Apr, 2026 Reviews received at journal 14 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviewers invited by journal 04 Apr, 2026 Editor assigned by journal 27 Feb, 2026 Submission checks completed at journal 27 Feb, 2026 First submitted to journal 26 Feb, 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. We do this by developing innovative software and high quality services for the global research community. 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