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arXiv · 2606.27355

RouterVLA: Budgeted Commissioning and Expert Onboarding for Growing VLA Pools

Xingyu Ren·Chugang Yi·Youran Sun
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Abstract

Robotic teams often maintain several vision-language-action policies but still deploy one global winner. We study two recurring decisions: which expert to deploy for a new condition and which candidate to add to the pool. RouterVLA combines a split-clean prior and outcome-disjoint probes with onboarding that credits only failures the incumbent pool cannot handle. Under an exactly cost-matched probe budget, it reaches 60.53\% held-out success, a $+1.64\pp$ gain over a semantic shortlist. Both criteria independently converge on the same five experts, confirming that the candidates best positioned to cover the base pool's blind spots are also broadly capable.

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Xingyu Ren, Chugang Yi, Youran Sun. 2026-06-25. RouterVLA: Budgeted Commissioning and Expert Onboarding for Growing VLA Pools. https://arxiv.org/abs/2606.27355

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