VLA-ZO: Fast Zeroth-Order Adaptation for Vision-Language-Action Models

Excerpt

arXiv:2610.06271v1 Announce Type: cross Abstract: Adapting vision-language-action (VLA) models to deployment-time distribution shifts is important for reliable robotic operation, but conventional first-order adaptation can exceed the memory budget of inference-oriented deployment platforms. Zeroth-order (ZO) optimization offers a forward-only alternative with inference-level memory, but accurate gradient estimation requires many perturbation queries, making naive ZO prohibitively slow for large