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ASD reveals that leveraging a teacher's optimization trajectory can significantly enhance student model performance by actively suppressing shortcut features.
By representing visual inputs as 3D Gaussian primitives, GST-VLA unlocks a new level of geometric understanding for vision-language-action models, leading to substantial performance gains in robotic manipulation tasks.
