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2,807 papers
If someone challenges an AI-made decision three years from now, could your organisation still show how it was made? For most, the honest answer is no. Models are replaced within a year or two, suppliers change hands, reference data is overwritten — while the decision itself lives on: a refused licence follows a person...
This repository contains the research data and supporting code associated with the article “A Mission-Oriented Explainable AI Metric Framework for Autonomous Military UAV Decision Support.” The deposited materials support two components of the study. First, they document the two-stream systematic evidence review used t...
A conceptual governance framework is developed that explains how explainable AI (XAI) improves algorithmic transparency, enhances consumer understanding, strengthens perceptions of fairness and ultimately builds consumer trust in AI-driven marketing analytics systems.
The solar system demands a clock running about 1.5e7 times proper time, a number nothing explained. We show it does not need explaining. The closure's two kinetic coefficients descend from a SINGLE logarithmic function P(X) = -(U/2) log(U - 2 d X) whose pole is a SPEED LIMIT, with 1/m_rel its Lorentz factor; and since...
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Analysis code, derived result tables, figures and validation-cohort inputs for a study of non-extensive (Tsallis) statistics in the glioblastoma transcriptome. Expression deviations of each sample are fitted with q-Gaussian laws by maximum likelihood. In a longitudinal GLASS cohort (230 libraries from 115 IDH-wildtype...
This repository contains the research data and supporting code associated with the article “A Mission-Oriented Explainable AI Metric Framework for Autonomous Military UAV Decision Support.” The deposited materials support two components of the study. First, they document the two-stream systematic evidence review used t...
The handling of acute lymphoblastic leukemia (ALL) which is the most common malignancy in children, depends on a prompt and precise diagnosis. Conventional techniques, such as bone marrow aspiration followed by flow cytometry, provide reliable results but have serious limitations. These include being invasive, requirin...
The solar system demands a clock running about 1.5e7 times proper time, a number nothing explained. We show it does not need explaining. The closure's two kinetic coefficients descend from a SINGLE logarithmic function P(X) = -(U/2) log(U - 2 d X) whose pole is a SPEED LIMIT, with 1/m_rel its Lorentz factor; and since...
Objective. Structured numeric review and unstructured textual audit evidence remain handled by largely disconnected systems, leaving a persistent gap between flagging an anomalous transaction and grounding that finding in applicable business or regulatory text. This study developed and evaluated a retrieval augmented A...
Accurate wind resource estimation in complex environments, such as the Colombian Caribbean, is challenging due to air–sea heat fluxes and nonlinear atmospheric dynamics. This systematic review and meta-analysis synthesized empirical evidence from 49 studies to evaluate whether advanced forecasting architectures (artifi...
The Framework for Emotional AI Risk (FEAR) Matrix is introduced, which categorizes EAI's psychological threats along two dimensions: Pathways of Harm (mind‐driven vs system‐driven) and Scope of Impact (individual, relational, and cumulative).
It is argued that machine learning should support human judgment instead of replacing it, and common machine learning methods and several human-centered requirements are discussed, including explainability, appropriate trust, usability, workflow integration, fairness, accountability, and human oversight.
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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