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2,807 papers
It is shown that fairness, accountability and transparency make distinct contributions to trust, while their combined contribution can also be represented as an overall FAT appraisal in the exploratory collective model.
The findings suggest that SMEs benefit from GenAI adoption when technological implementation is supported by entrepreneurial behavior and adaptive organizational practices, and when technological implementation is supported by entrepreneurial behavior and adaptive organizational practices.
In silico NAMs, including computational approaches, can contribute to the development of novel Safe and Sustainable by Design chemicals and substances by identifying potentially hazardous ones at an early stage by identifying potentially hazardous ones at an early stage.
The XAI-assisted Recurrent neural network Attribution for Channel Estimation (X-RACE) framework is proposed, and novel temporal XAI metrics: Saturation Time, Importance Drift, and Relevance Contrast are proposed to characterize the LSTM's learning dynamics and memory convergence.
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This work applies a hierarchical clustering algorithm to analyse whether representations learned by a speaker recognition network from utterances naturally form hierarchical clusters, and proposes a new task, second-order pattern recognition, to identify which discovered second-order patterns characterising known utter...
In February 2024 the U.S. Federal Communications Commission (FCC) placed AI-generated voices under the Telephone Consumer Protection Act (TCPA). Yet no peer-reviewed measurement says how much unwanted call traffic is placed by a machine, or how much of that machine speech is synthesized rather than played from a record...
A novel PA-associated molecular axis in AD is revealed, with HDAC3 serving as a central epigenetic-metabolic regulator within astrocytes and being identified as a potential therapeutic target for AD.
A PRISMA-guided systematic review of 127 peer-reviewed studies to examine how machine learning (ML), deep learning (DL), Natural Language Processing (NLP), and Explainable AI (XAI) are transforming ESG rating analysis develops a tripartite framework classifying studies by the functional role of the ESG score.
Using the mission-oriented innovation policy system (MOIPS) for research and development (R&D) at the national level, this study explains how and when R&D spending on sustainable energy technologies drives the clean energy transition (CET). The study utilises second-generation unit root tests, the Westerlund...
This research presents a machine learning approach to predict the capacity degradation of lithium-Ion battery, integrated with Explainable AI to improve model explainability and shows that charge time has the most impact on capacity degradation prediction.
This paper distinguishes technical reliability from trust in AI-supported clinical decision-making, arguing that the two belong to distinct registers that current debates tend to elide and proposes replacing the expression "trustworthy AI" with "technically reliable AI," a distinction that relocates the conditions of t...
An agility paradox linking reactive, efficiency-oriented AI adoption to potential constraints on proactive agile capabilities is developed, linking reactive, efficiency-oriented AI adoption to potential constraints on proactive agile capabilities.
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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