# Preprint reports fewer simulator runs with AI-assisted calibration

_Published Monday, October 19, 2026 at 5:51 AM EDT · AI, Science · Latest · Tier 2 — Notable_

Researchers report in a preprint that a workflow combining a language model with a conventional optimizer reached target calibration accuracy in 9 simulator runs, compared with 12 for the language model alone, 17 for Nelder-Mead and more than 60 for Bayesian optimization. Calibration adjusts simulator parameters to match reference data.

The study tested a cylinder-wake simulation and a damped-oscillator problem. The language model used descriptions of physical errors to suggest initial parameter changes, then passed accumulated evaluations to a conventional optimizer. Its early advantage disappeared by fifteen evaluations, and variability in language-model outputs produced a 9.8-fold performance spread.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2610.22379)

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Canonical: https://techandbusiness.org/newswire/StJfxXh-0-ShymC7GbERa-
Published: 2026-10-19T09:51:50.676Z
Story chronology: 2026-10-19T04:00:00.000Z
Retrieved: 2026-10-19T13:16:08.540Z
Publisher: Tech & Business (techandbusiness.org)