Attention layers--which map a sequence of inputs to a sequence of outputs--are core building blocks of the Transformer architecture which has achieved significant

We show that such a random-feature attention layer can express a broad class of target functions that are permutation invariant to the key vectors.

Oct-8-2025, 07:44:13 GMT

Title
274db6bf1b01d8b4f07feaeb8c46f474-Supplemental-Conference.pdf
Attention layers--which map a sequence of inputs to a sequence of outputs--are core building blocks of the Transformer architecture which has achieved significant
Attention layers--which map a sequence of inputs to a sequence of outputs--are core building blocks of the Transformer architecture which has achieved significant

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