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arXiv AI By Yoojin Oh, Jeongsol Kim, Yeonwoo Seo, Jangho Park, Seonghyun Jin, Sunwoo Park, Youngmin Kim, Youngjun Jun, Kyumin Choi, Jong Chul Ye

FastOPD: On-Policy Distillation for Lightweight VLA Deployment

Read the original on arXiv AI →

FastOPD is a framework that distills large Vision‑Language‑Action (VLA) models into lightweight versions by using on‑policy distillation with a flow map and a self‑consistency objective. The method trains a compact student to mimic the teacher’s dynamics, achieving performance close to the teacher while drastically reducing inference steps. Experiments on LIBERO, RoboTwin 2.0, and real‑robot deployments show significant latency reductions and higher success rates compared to existing few‑step distillation baselines.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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