Stability of Measure-to-Measure Transformers on Sub-Gaussian Data

Excerpt

arXiv:2610.07717v1 Announce Type: cross Abstract: Transformers have exhibited impressive empirical success across various domains, but their theoretical foundations remain less developed. This work constitutes a mathematical study of the measure-to-measure operators defined by transformers. We show that transformers map sub-Gaussian inputs to sub-Gaussian outputs; this ensures that taking arbitrary-length compositions of the softmax operator is well-defined. We then show that transformers are H\