AIBullisharXiv – CS AI · 10h ago7/10
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Weakly Supervised Concept Learning for Object-centric Visual Reasoning
Researchers present a weakly supervised learning approach that combines neural networks with symbolic AI for object-centric reasoning tasks, requiring only 1% of typical labels while outperforming foundation models in domain generalization. The method bridges perception and logical reasoning by using slot-based architectures and VAEs to ground symbolic outputs for frameworks like Inductive Logic Programming.