VLA Fine-Tune

Key Insight

Fine-tuning a pretrained Vision-Language-Action (VLA) model adapts its broad generalist capabilities to a specific robotic platform with a fraction of the demonstrations required for from-scratch Behavior Cloning (BC). Because the base model already possesses rich visual features and language understanding, the fine-tuning process only needs to align its tokenized action vocabulary with the joint spaces and kinematic limits of the target robot. This makes VLA adaptation highly sample-efficient and robust to visual clutter compared to training a task-specific policy from scratch.