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cs.RO2026
FastOPD: On-Policy Distillation for Lightweight VLA Deployment
Yoojin Oh, Jeongsol Kim, Yeonwoo Seo +7
Vision-Language-Action (VLA) foundation models have scaled rapidly to enhance manipulation performance and generalizability, but this scaling incurs high computational costs that r…
cs.RO2026
DriftOPD: Sequence-Level Reverse-KL Distillation for One-Step VLA Policies
Youngjun Jun, Kyumin Choi, Youngmin Kim +4
Vision-Language-Action (VLA) models increasingly rely on action experts that generate short action chunks under receding-horizon control. While chunk-level training is convenient a…
cs.RO2026
Don't Throw Away the Tail: Action Upcycling for Policy Acceleration
Taesung Kwon, Jangho Park, Sunwoo Park +5
Modern robot policies predict a chunk of future actions from a single observation, execute only a prefix, and discard the rest before replanning. Choosing the length of this prefix…