RL²-VLA boosts robot manipulation via RL steering
rsasaki0109 · x · 2026-08-18
RL²-VLA is an adaptive inference-time steering framework that improves robotic manipulation by applying Reinforcement Learning on VLA latents. It trains a lightweight offline RL flow-matching policy and steers the base VLA during inference. The method activates compositional steering mainly when failure is predicted. Benchmarks show average success rate improvements of 10.1% on SIMPLER, 8.9% on PolaRiS, and 19.5% on real robots.
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