SOURCE-LINKED INTELLIGENCE

SMILE: Smooth Motion for Improved Long-Horizon VLA Execution

arXiv · AI, language, vision and robotics · article · Aug 29, 2026 · UTC

Vision-Language-Action (VLA) models reduce inference cost by executing multiple actions per call, but longer horizons often degrade accuracy because raw chunks contain jitter and outliers. We introduce SMILE, an architecture-preserving interface that predicts B-spline coefficients and decodes them into smooth action sequences. SMILE changes only the action representation, enabling longer fixed horizons while retaining each baseline's backbone and model scale. We apply SMILE to SmolVLA, Evo1, VPP, and DAWN, improving accuracy and amortized inference efficiency across LIBERO, CALVIN, and real-wo

Read original source ↗ Open in workspace

recordType

paper

region

Global