ControlVLA adapts a DROID-pretrained diffusion VLA policy to new manipulation tasks with 10 to 20 demos by injecting object-centric features through zero-initialized cross-attention layers, achieving 76.7% success across six short-horizon tasks.
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ControlVLA: Few-shot Object-centric Adaptation for Pre-trained Vision-Language-Action Models
ControlVLA adapts a DROID-pretrained diffusion VLA policy to new manipulation tasks with 10 to 20 demos by injecting object-centric features through zero-initialized cross-attention layers, achieving 76.7% success across six short-horizon tasks.