Bettina Finzel

Weakly supervised concept Bottleneck Learning for Robust Two stage Object centric visual reasoning

This work introduces the Dynamic Orthogonal Concept Bottleneck (D-OCB), an object-centric slot- VAE framework designed to extract human-aligned symbolic predicates under extremely weak supervision and achieves high concept alignment and downstream visual reasoning accuracy using minimal label budgets, matching or outpe...