178 citations · 196 across the 7 of their papers we have counts for
9 papers
Towards a Unified Multidimensional Explainability Metric: Evaluating Trustworthiness in AI Models
Georgios Makridis, Georgios Fatouros, Athanasios Kiourtis +4
In this paper, we present a comprehensive framework for assessing the explainability of various XAI methods, such as LIME and SHAP, across multiple datasets and machine learning mo…
Persistent and Conversational Multi-Method Explainability for Trustworthy Financial AI
Georgios Makridis, Georgios Fatouros, John Soldatos +2
Financial institutions increasingly require AI explanations that are persistent, cross-validated across methods, and conversationally accessible to human decision-makers. We presen…
Native Explainability for Bayesian Confidence Propagation Neural Networks: A Framework for Trusted Brain-Like AI
Georgios Makridis, Georgios Fatouros, John Soldatos +2
The EU Artificial Intelligence Act (Regulation 2024/1689), fully applicable to high-risk systems from August 2026, creates urgent demand for AI architectures that are simultaneousl…
HumAIne-Chatbot: Real-Time Personalized Conversational AI via Reinforcement Learning
Georgios Makridis, George Fragiadakis, Jorge Oliveira +4
Current conversational AI systems often provide generic, one-size-fits-all interactions that overlook individual user characteristics and lack adaptive dialogue management. To addr…
VirtualXAI: A User-Centric Framework for Explainability Assessment Leveraging GPT-Generated Personas
Georgios Makridis, Vasileios Koukos, Georgios Fatouros +1
In today's data-driven era, computational systems generate vast amounts of data that drive the digital transformation of industries, where Artificial Intelligence (AI) plays a key…
XAI for All: Can Large Language Models Simplify Explainable AI?
Philip Mavrepis, Georgios Makridis, Georgios Fatouros +3
The field of Explainable Artificial Intelligence (XAI) often focuses on users with a strong technical background, making it challenging for non-experts to understand XAI methods. T…
Enhancing Explainability in Mobility Data Science through a combination of methods
Georgios Makridis, Vasileios Koukos, Georgios Fatouros +1
In the domain of Mobility Data Science, the intricate task of interpreting models trained on trajectory data, and elucidating the spatio-temporal movement of entities, has persiste…
XAI for time-series classification leveraging image highlight methods
Georgios Makridis, Georgios Fatouros, Vasileios Koukos +3
Although much work has been done on explainability in the computer vision and natural language processing (NLP) fields, there is still much work to be done to explain methods appli…
Transforming Sentiment Analysis in the Financial Domain with ChatGPT
Georgios Fatouros, John Soldatos, Kalliopi Kouroumali +2
Financial sentiment analysis plays a crucial role in decoding market trends and guiding strategic trading decisions. Despite the deployment of advanced deep learning techniques and…