[2603.01235] Extended Empirical Validation of the Explainability Solution Space

Computer Science > Artificial Intelligence arXiv:2603.01235 (cs) [Submitted on 1 Mar 2026] Title:Extended Empirical Validation of the Explainability Solution Space Authors:Antoni Mestre, Manoli Albert, Miriam Gil, Vicente Pelechano View a PDF of the paper titled Extended Empirical Validation of the Explainability Solution Space, by Antoni Mestre and Manoli Albert and Miriam Gil and Vicente Pelechano View PDF HTML (experimental) Abstract:This technical report provides an extended validation of the Explainability Solution Space (ESS) through cross-domain evaluation. While initial validation focused on employee attrition prediction, this study introduces a heterogeneous intelligent urban resource allocation system to demonstrate the generality and domain-independence of the ESS framework. The second case study integrates tabular, temporal, and geospatial data under multi-stakeholder governance conditions. Explicit quantitative positioning of representative XAI families is provided for both contexts. Results confirm that ESS rankings are not domain-specific but adapt systematically to governance roles, risk profiles, and stakeholder configurations. The findings reinforce ESS as a generalizable operational decision-support instrument for explainable AI strategy design across socio-technical systems. Subjects: Artificial Intelligence (cs.AI); Software Engineering (cs.SE) Cite as: arXiv:2603.01235 [cs.AI]   (or arXiv:2603.01235v1 [cs.AI] for this version)   https://doi.org/10.485...