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The Transformer as a Polar State Estimator

Racioppo, Peter
arXiv (All) · Papers
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artificial-intelligencemachine-learning
We show that the core components of the Transformer---attention, residual connections, and normalization---arise naturally from a single geometric state estimation problem. Modeling the latent state in polar coordinates naturally separates radial and hyperspherical dynamics, yielding a precision-wei
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