AINeutralarXiv – CS AI · 7h ago6/10
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BRo-JEPA: Learning Modular Arithmetic in Latent Space
Researchers introduce BRo-JEPA, a neural network architecture that learns modular arithmetic rules by imposing circular structure in latent space, achieving 99.46% zero-shot generalization on unseen operations. The work demonstrates that neural networks can learn abstract algebraic rules rather than merely memorizing patterns when architecture aligns with problem structure.