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cs.LG2026
Revisiting Explainable AI through Model-Independent Concept Dictionaries
Thomas Schnake, Doreen Schöppenthau, Alexander Meyer +3
Modern applications of AI rely on increasingly complex models. Explainable AI (XAI) has emerged as a set of techniques aimed at improving model transparency. However, existing XAI…
cs.LG2026
ReLaG: A Scalable Framework Generalizing Random Splits to Data with Latent Relations
Anthony Lavertu, Jacob Cote, Sophie Gobeil +3
Random splitting can yield non-independent train--test subsets when a dataset contains related samples, as is common in certain applications such as biochemical studies. This leads…