HyT, a hyperbolic Transformer, is claimed to be universally consistent for L2 regression, but the proof is invalidated by an algebraic error and circular reasoning.
Nearly-tight vc-dimension and pseudodimension bounds for piecewise linear neural networks,
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Transformers Are Universally Consistent
HyT, a hyperbolic Transformer, is claimed to be universally consistent for L2 regression, but the proof is invalidated by an algebraic error and circular reasoning.