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2,254 papers
The design pairs cognitive adaptivity, realised as mastery-based task selection under configurable parameters, with motivational design grounded in Keller’s ARCS model, and a formalised adaptation logic linking learner states, adaptive responses, and conjectures.
The plant phenotyping workflow of the Orchestrated Platform for Autonomous Laboratories is explored, which couples Oak Ridge National Laboratory's Advanced Plant Phenotyping Laboratory with the Frontier supercomputer and replaces roughly twelve hours of manual analysis with interactive queries returning in seconds to m...
A comprehensive, AI-enhanced training framework designed to standardize and accelerate the education of clinicians, surgeons, and embryologists and integrate six core domains, including adaptive learning for theoretical knowledge, AI-driven simulations for clinical decision-making, virtual reality for surgical and embr...
Artificial intelligence and complementary digital health technologies have the potential to improve travel healthcare throughout the travel continuum and current evidence remains largely retrospective, highlighting the need for prospective multicenter implementation studies evaluating clinically meaningful outcomes.
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STRIDE, a machine-learning framework for sepsis detection across seven hospitals with a scalable approach to label quality, outperformed SOFA and Epic on discrimination and showed favorable calibration by Brier score, while retaining strong discrimination among SIRS-positive non-septic encounters.
Experiments on eight code generation benchmarks show that CGMIA outperforms eight existing membership inference methods in most cases, and effectively detects known leaked APPS samples in StarCoder-7B's training data.
AMEND predicts each block's BLASST verdict from margins audited at earlier steps, so the GPU fetches only predicted survivors while near-bank PIM units in high-bandwidth memory (HBM) concurrently score the omitted complement.
This study analyzes annual reports of firms listed on Borsa Istanbul (BIST) for the period from 1990 to 2026, and demonstrates that data-driven initia’sation significantly improves topi’sc interpretability, reduces optimization iterations, decreases model uncertainty, and en’hances reproducibility compared with tr...
The review synthesizes empirical evidence on learner autonomy, self-regulation, and metacognitive development to identify the pedagogical, technical, cultural, and institutional factors influencing implementation in Arab classrooms and concludes that success hinges on pedagogy and cultural appropriation rather than tec...
AlignCP is proposed, a framework that reconciles supervised few-shot adaptation with conformal uncertainty estimation under non-exchangeability and learns a reweighted calibration distribution that reduces the score-level discrepancy between the labeled support set and the unlabeled query set.
A published artifact with a DOI cannot be revised; only the errata can. Errata therefore drift away from the primary source over time: a quotation loses a word, occurrences are undercounted, an item declared unresolvable is quietly marked resolved, and the last-updated stamp goes stale. This tool turns that drift into...
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
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