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arXiv Machine Learning By Haotian Yan, Jiaqi Liu, Bingyi Jing, Tianjun Yao

Response-Informed Value Estimation for Cost-Aware Multi-Turn LLM Routing

Read the original on arXiv Machine Learning →

The paper introduces RIVET, a method for multi‑turn large language model routing that uses post‑call responses to train two value estimators: a deployable Routing Value Estimator that operates on pre‑call information, and a training‑only Response‑Informed Value Estimator that also observes the actual response. By conditioning on the response, RIVET turns response‑induced return variation into an observable covariate, reducing asymptotic estimation error. Experiments on the MINT benchmark show that RIVET solves more held‑out tasks than the strongest baseline while cutting total call cost by 74.7%.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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