2 papers
cs.HC2025
MetaExplainer: A Framework to Generate Multi-Type User-Centered Explanations for AI Systems
Shruthi Chari, Oshani Seneviratne, Prithwish Chakraborty +2
Explanations are crucial for building trustworthy AI systems, but a gap often exists between the explanations provided by models and those needed by users. To address this gap, we…
cs.AI2024
An Ontology-Enabled Approach For User-Centered and Knowledge-Enabled Explanations of AI Systems
Shruthi Chari
Explainable Artificial Intelligence (AI) focuses on helping humans understand the working of AI systems or their decisions and has been a cornerstone of AI for decades. Recent rese…