Apple's REFACTOR-VLA: Robots Learn Reusable Libraries of Typed Motor Programs
Apple ML Research · rss · 2026-09-02
Apple ML Research presents REFACTOR-VLA. Current VLA models (OpenVLA, π0, RT-2, RDT-1B) are monolithic—they emit raw motor commands without reusable behavioral abstractions, performing poorly on long-horizon tasks and resisting interpretation. The work learns typed motor program libraries unsupervised, tackling the core problem existing approaches like AtomicVLA and AtomSkill avoid: deciding when two action sequences are behaviorally equivalent.
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