Johnny tokenizes RPM images into a learned codebook, adds a self-referential 'sub-enumeration' loss to the reasoning module, and pairs it with a new Spin-Transformer layer; gains over strong baselines are modest, and a metadata-based generalization result is suspicious.
Deep Residual Learning for Image Recognition
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Johnny: Structuring Representation Space to Enhance Machine Abstract Reasoning Ability
Johnny tokenizes RPM images into a learned codebook, adds a self-referential 'sub-enumeration' loss to the reasoning module, and pairs it with a new Spin-Transformer layer; gains over strong baselines are modest, and a metadata-based generalization result is suspicious.