# RIVET preprint reports more solved tasks with 74.7% lower model-call cost

_Published Monday, October 19, 2026 at 6:30 AM EDT · AI, Science · Latest · Tier 2 — Notable_

Researchers report that RIVET, a system for choosing language models during multi-turn tasks, solved more held-out MINT benchmark tasks than the strongest multi-turn baseline while using 74.7% less total call cost.

The method uses responses recorded in past interactions to train a model-selection system. A training-only estimator observes the response each model produced, helping a separate estimator learn which model to select before a call. At deployment, routing uses only information available before the response arrives. The result is a preprint benchmark finding, with the reported cost comparison confined to MINT.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2610.23239)

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Canonical: https://techandbusiness.org/newswire/wXFZScpZh794vRrCqjiyVq
Published: 2026-10-19T10:30:56.132Z
Story chronology: 2026-10-19T04:00:00.000Z
Retrieved: 2026-10-19T13:22:04.054Z
Publisher: Tech & Business (techandbusiness.org)