explainable ai

Mobile Generative AI Literacy and English Writing Self-Efficacy: The Role of AI Feedback Engagement in Higher Education

This study examines the relationship between mobile Generative Artificial Intelligence (GenAI) literacy and English writing self-efficacy (EWSE) among university students, with AI feedback engagement (AFE) proposed as a mediating mechanism. Using a quantitative cross-sectional design, data were collected from 312 unive...

Mechanistic Interpretability and Explainable AI (XAI) in Foundation Models: Reverse-Engineering Circuits, Superposition, and Safety Bounds

Abstract—Foundation models, particularly autoregressive Transformer Large Language Models (LLMs) and Vision-Language Models (VLMs), have exhibited unprecedented reasoning and generative capabilities across computer science and engineering. However, their internal representations operate as opaque, high-dimensional 'bla...

Use of generative Artificial Intelligence tools in medical student research projects: An activity system analysis.

This study aimed to characterise how generative AI is reshaping the activity of learning to do research within a mandatory medical student research project, and to identify the contradictions driving that change.

Explaining FOMO Symptoms Based on Maladaptive Perfectionism and Emotional Loneliness with Emphasis on the Mediating Role of Artificial Intelligence Dependency among Female High School Adolescents

Objective: The present study aimed to explain FOMO (Fear of Missing Out) symptoms based on maladaptive perfectionism and emotional loneliness, with a particular focus on the mediating role of artificial intelligence dependency among female high school adolescents. Methods and Materials: This correlational study employe...

Explainable automated classification of cervical cancer cells using SE-LGANet with squeeze and excitation blocks and local and global attention mechanisms

A Convolutional Neural Network integrated with Squeeze-and-Excitation blocks and dual attention mechanisms was developed to classify five distinct cell types, providing an explainable and systematically validated approach for cervical cell evaluation.

An explainable semi-supervised self-training approach for hardware Trojan detection using LIME

An Explainable Semi-Supervised Self-Training approach for HT detection in the pre-silicon IC phase is proposed, which effectively handles the scarcity of labeled training data by leveraging both labeled and unlabeled samples and a hybrid ADASYN-ENN sampling strategy is proposed.

Forecasting spatio-temporal wildlife strike risk for aviation safety using explainable AI

Interpretable Smart Shelf: AI-Driven Food Shelf Life and Quality Prediction

Interpretable SmartShelf is proposed—a non-invasive machine learning algorithm for food classification, freshness detection, and shelf-life estimation based on RGB images that provides the user with an interpretable interface to visualize the predictions.

Explainable machine learning models for AI enabled credit scoring and financial inclusion in emerging markets

Findings support explainability- and governance-centered model selection for inclusive credit scoring, while underscoring the need for multi-metric fairness auditing, external validation, and continued monitoring in operational deployment.

Foundations of Translation: For EFL University Students

Foundations of Translation: For EFL University Students introduces Arabic–English translation in both directions for Arabic-speaking undergraduates across the Arab world. It develops the ability to analyze a source text, understand a translation brief, compare possible renditions, and explain decisions using evidence....

Foundations of Children's Literature: For EFL University Students

Foundations of Children’s Literature: For EFL University Students introduces the study of literature for young readers through adult, university-level analysis. It serves international EFL students, assumes no previous university course in the subject, and explains necessary concepts in clear B2-oriented academic Engli...

Large Language Models in Cybersecurity

Large Language Models (LLMs) serve as general-purpose interfaces across security operations,threat intelligence,vulnerability & malware analysis,secure coding,and penetration testing by summarizing evidence & aiding analyst reasoning.Despite rapid adoption,challenges persist in data quality,domain adaptation,privacy,re...