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#machine learning Preprint Oct 2026

Counting with Attention and LayerNorm: Norm Scaling and Representation Geometry

Counting is a simple task on which transformers can nevertheless fail at long sequence lengths. We study the cost of counting in a single attention layer, up to a maximum length $L$, focusing on how softmax attention and layer normalization shape the representation from which the count is recovered. We mainly focus on...

A. Shaffy, Manoj Dhakal, Safal Shrestha et al. · 0 citations

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