Author

Alexander Hsu

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Preprint Aug 2026

Training-Free Universal Approximation by Prompting Random Transformers

How expressive is prompting a transformer? Answering this question is important for separating the roles of prompting, architecture, and pretraining in transformer models, and for determining whether task-specific behavior must be stored in model weights or can instead be induced at inference time through the prompt. W...

Alexander Hsu, Rong-Jie Lai · 1 citation

Preprint Sep 2026

Approximating Measures on Function Spaces: Transport and Truncation

This work introduces the class $\mathcal{P}_\psi(\mu)$ of measures that differ from a reference measure only through a finite-dimensional map $\psi$ while preserving the reference conditionals on its fibers, and develops approximation theory for fitting within it.

R. Baptista, Bamdad Hosseini, Alexander Hsu · 0 citations