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ForceDelta-VLA: Distilling Force-Conditioned ActionCorrections for Contact-Rich Manipulation

arXiv · AI, language, vision and robotics · article · Sep 16, 2026 · UTC

Force-aware Vision-Language-Action (VLA) policies improve contact-rich manipulation, but typically combine task-level motion and contact-dependent adjustment in a single action prediction. Demonstrations provide no explicit labels for decomposing that prediction into a reusable reference action and a correction. We present ForceDelta-VLA, a correction-distillation framework that constructs an explicit force-correction target using paired predictions from a frozen teacher's force-conditioned and learned force-agnostic modes. A separate delay-correction target accounts for reference-action misma

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