Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …

We introduce a novel model-agnostic post-hoc Explainable AI method that provides
meaningful interpretations for hidden neuron activations in a Convolutional Neural Network …

A major challenge in Explainable AI is in correctly interpreting activations of hidden neurons:
accurate interpretations would provide insights into the question of what a deep learning …

Abstract Explainable Artificial Intelligence (XAI) poses a significant challenge in providing
transparent and understandable insights into complex AI models. Traditional post-hoc …

Identification of threatening comments on social media platforms has recently gained
attention. Prior approaches have addressed this task in some low-resource languages but …

Knowledge Graphs (KG) are the backbone of many data-intensive applications since they
can represent data coupled with its meaning and context. Aligning KGs across different …

Recent advances in AI--including generative approaches--have resulted in technology that
can support humans in scientific discovery and decision support but may also disrupt …

Recently, studies related to human activity recognition have developed which have been
applied in various fields. In that field Machine learning and deep learning techniques have …

In this study, the capability of Large Language Models (LLMs) is explored to automate
Concept Induction, a process traditionally reliant on formal logical reasoning using …