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2,487 papers
This paper investigates the application of Explainable Artificial Intelligence (XAI) to enhance system security. Traditional security systems often rely on opaque "black box" AI models, hindering effective threat detection and defense. This work proposes a system architecture leveraging XAI techniques to provide interp...
Current Explainable AI (XAI) techniques frequently generate explanations that are merely post-hoc justifications for model predictions, lacking a deep understanding of the model's reasoning process. This paper proposes a novel approach to XAI based on the construction of Causal Bayesian Networks (CBNs). CBNs are employ...
This is the initial release of "dogo-tutor," an AI tutor designed for coding education. This release is created to archive the repository and obtain a DOI via Zenodo. Key Features Provides step-by-step hints (problem clarification, strategy, logic structuring, and partial code) rather than direct answers. Designed to o...
Coexisting safely with unpredictable Artificial Intelligence (AI) remains a foundational challenge for contemporary AI ethics. This paper proposes “stable otherness” as a relational framework that re-centers alignment on sociotechnical structures. Rather than treating AI as an autonomous conscious agent, we define AI a...
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The rapid convergence of artificial intelligence (AI) workloads, high-density computing, advanced liquid and air cooling, increasingly distributed electrical architectures, and stringent availability requirements is transforming the data centre from a predominantly passive infrastructure environment into a highly dynam...
Chemical safety in the Republic of Korea is governed by five acts falling under the purview of the Ministry of Climate, Energy, and Environment (MCEE): the Act on Registration and Evaluation of Chemicals (K-REACH Act), the Chemicals Control Act (CCA), the Environmental Health Act, the Environmental Damage Relief Act, a...
The construction of health indicators (HIs) for failure prognostics is crucial for monitoring and predicting the health state of multi-component systems. Recently, data-driven methods for HI construction and prognostics have gained increasing attention, both relying heavily on high-quality run-to-failure (RTF) data for...
This survey explores the use of Machine Learning (ML) in the field of Computer Algebra (CA), both to optimise existing CA algorithms, and to perform symbolic computation directly. Traditional symbolic methods, while mathematically rigorous, often are computationally expensive thus limiting their use in real-world appli...
Abstract Effective Pavement Management System (PMS) planning depends on the ability to anticipate both the severity and physical extent of multiple distress types under real-world data constraints. This work introduces an interpretable dual-stage Deep Learning (DL) framework that sequentially classifies distress severi...
Coexisting safely with unpredictable Artificial Intelligence (AI) remains a foundational challenge for contemporary AI ethics. This paper proposes “stable otherness” as a relational framework that re-centers alignment on sociotechnical structures. Rather than treating AI as an autonomous conscious agent, we define AI a...
This independently citable appendix contains specification and deployment detail for the AEGIS v1 interoperability profile: the complete design-principle catalog, architecture and adapter tables, extension configurations, split-view case analysis, byte-level field semantics, security assumptions, and verification inter...
The problems of this paper are the problems of this paper, and some future directions for constructing a reliable cardiac disease prediction system with clinical applications are proposed.
In a new book, Professor Eric So explores how the technology affects our thinking skills.
Earth AI
GPT-Lab
· gpt-lab.eu
Oct 14, 2026
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.
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.
Professor Deb Roy contends there should be someone who is “answerable” for every piece of text in public life, no matter its origins.
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.
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