Energy-Gated Attention and Wavelet Positional Encoding: Complementary Inductive Biases for Transformer Attention

arXiv:2605.26355v1 Announce Type: new Abstract: Standard transformer attention computes pairwise token similarity but treats all tokens as equally salient and all positions as equally local, regardless of the informational structure of the input. We identify two complementary inductive biases that standard attention lacks: energy salience (which tokens concentrate informational energy, learned end-to-end without explicit frequency decomposition) and scale-selective locality (how far positional influence extends at each frequency, implemented via Morlet wavelet encoding). We address both with t

Source: arXiv cs.LG — read the full report at the original publisher.

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