Moose: Latent concept learning with reasoning-shortcut awareness in $\mathcal{EL}^{++}$
Moose improves over propositional-NeSy, fuzzy-logic, and ontology embedding baselines, and presents the first reasoning-shortcut analysis in an OWL EL setting.
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Moose improves over propositional-NeSy, fuzzy-logic, and ontology embedding baselines, and presents the first reasoning-shortcut analysis in an OWL EL setting.
Baobab is presented, which is to the authors' knowledge the first to characterize and mitigate reasoning shortcuts in a non-Horn description logic and machine-checked in Lean 4.
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