A VAE and slot-attention scheme learns interpretable object concepts from 1% labels, enabling symbolic reasoning that outperforms foundation models under domain shift.
Deepproblog: Neu- ral probabilistic logic programming
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Weakly Supervised Concept Learning for Object-centric Visual Reasoning
A VAE and slot-attention scheme learns interpretable object concepts from 1% labels, enabling symbolic reasoning that outperforms foundation models under domain shift.