ScoutRoute: Efficient Mixture-of-Experts Routing Using Internal Language Model Signals

ScoutRoute is a lightweight post‑hoc routing framework for Mixture‑of‑Experts systems that predicts expert competence using internal language model signals from a single forward pass of a scout model. It employs hidden‑state representations with logistic probes and logit‑derived confidence measures in a domain‑aware routing strategy, avoiding modifications to the underlying language models. Experiments on five open‑weight language models across four benchmark datasets show that ScoutRoute consistently outperforms individual routing signals and achieves superior calibration with only one scout‑model inference.

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