This academic paper presents a method that combines explainable artificial intelligence (XAI) techniques with adaptive learning to improve energy consumption prediction models. The method focuses on handling shifts in data…
Continue readingThe paper introduces a novel approach to Intrusion Detection Systems (IDS), called X-CBA. This approach leverages the advantages of Graph Neural Networks (GNNs) to effectively process network traffic data while…
Continue readingThe research focuses on Explanatory Model Steering (EXMOS), a method to fine-tune prediction models using Explainable AI and Interactive Machine Learning. The study investigates the effectiveness of global model-centric and…
Continue readingThe authors discuss the need for explainable AI systems, focusing on counterfactual explanations that are often used post-decision. They argue that these explanations often lack plausibility, hence limiting their value….
Continue readingThe paper presents a new approach to make Explainable Artificial Intelligence (XAI) more accessible to a wider audience, including non-experts. The researchers developed a Large Language Model (LLM) using ChatGPT…
Continue readingThe article explores the gap between the information provided by AI systems and the information needs of people affected by algorithmic decision-making. It introduces the ‘XAI Novice Question Bank’, a…
Continue readingThe paper presents an analysis of contribution functions for quantitative bipolar argumentation graphs. These functions quantify how one argument contributes to another. The analysis introduces principles that formalize the intuitions…
Continue readingThe paper titled ‘Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks’ explores the issue of feature removal in Explainable AI (XAI). It highlights how occlusion strategies can vary…
Continue readingThe paper addresses the issue of unfaithfulness in the explanations provided by visual question answering (VQA) systems. Current post-hoc methods, which provide natural language explanations (NLE), often fail to align…
Continue readingThe paper investigates the creation of multi-agent strategy explanations to improve human-robot collaboration. It emphasizes the increasing importance of robots’ ability to collaborate fluently with humans, especially in social, home,…
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