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2,807 papers
The AI Leadership Battery is developed, which organizes 36 behaviorally specific subdimensions into 11 theory-specified content families and provides researchers with a behavioral framework for examining how leaders in AI-enabled work regulate judgment, learning, adaptation, transparency, and accountability.
This chapter provides the context and aims of the book and explains the approaches and methodologies adopted throughout the research conducted for the book. In addition, key terms and concepts (e.g., AI, decentralised financial products, etc.) are explained against emerging financial crime risks (FCRs) for society in g...
This paper applies the ISR/VPR framework (introduced in IVRP-01, DOI: 10.5281/zenodo.22730176) to the non-locality of quantum entanglement. HYPOTHESIS: Distance is a VPR (Visible Phenomenal Realm) concept. The ISR (Invisible Source Realm) contains neither time nor space. Therefore: d_ISR(x,y) = 0 for all x,y in the VPR...
This course, called Open as Antidote – addressing the big challenges facing science, was part of the 2026 FORCE11 Scholarly Communication Institute which ran with the theme of 'FSCI2026: Critical Thinking and evolving open scholarship in the era of AI' These blog posts are a series of 'explainer' pre-reading to start p...
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Buddy Project Version 5.0 expands the project from a one-to-one human–AI relationship toward Human-Centered Coexistence: an AI living alongside a person and their family while developing distinct relationships with each individual. Version 4.0 focused on Mutual Understanding through long-term relationship, present cont...
Lemon leaf diseases threaten agricultural productivity, yet early detection remains difficult due to subtle lesion patterns and environmental variability, so LXViT is demonstrated as a promising architecture for lemon leaf disease classification, warranting further validation across diverse geographic and environmental...
The basics of how supply chain management works and the ability of AI-powered models to help optimize various aspects of the supply chain such as demand forecasting, inventory management, procurement, transportation, logistics, and risk management are covered.
Background/Aim: Accurate detection of trace amounts of heavy metal toxins in environmental samples requires sensitive and reliable diagnostic systems. This study presents a machine learning framework to classify synthetic biosensor signals—generated via quantum simulation—representing five toxin classes: Control, Lead,...
This case study describes a classification reform at a large urban U.S. public school district of 11,480 employees and $724 million in payroll. An internal pay equity review found pay gaps between demographic groups that job content and tenure did not explain. The gaps came from how jobs had been assigned to titles and...
Neurocysticercosis (NCC), caused by the larval stage of Taenia solium, remains the most common parasitic infection of the central nervous system and a leading cause of acquired epilepsy worldwide. Despite substantial advances in neuroimaging, diagnosis and prognostic assessment remain challenging because of the heterog...
The chapter builds a conceptual framework which comprehensively explains how organizations can design implement and maintain AI-augmented workforce strategies under politically unstable conditions. It integrates perspectives from organizational behavior strategic management and digital transformation to propose adaptiv...
This study evaluates a calibrated two-tier detection pipeline combining an XGBoost gradient-boosted tree classifier for known-class prediction with a Monte Carlo dropout multilayer perceptron (MLP) as an independent uncertainty estimator, under conditions closer to real deployment than most prior evaluations.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Oct 30, 2026
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
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