Reasoning shortcuts in neurosymbolic learning are formalized as constraint satisfaction problems; an ASP-based verifier checks unique concept mappings, a greedy repair adds constraints, and complexity plus sample bounds are derived.
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Constraint-Based Analysis of Reasoning Shortcuts in Neurosymbolic Learning
Reasoning shortcuts in neurosymbolic learning are formalized as constraint satisfaction problems; an ASP-based verifier checks unique concept mappings, a greedy repair adds constraints, and complexity plus sample bounds are derived.