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The data pyramid framework reveals how the interplay of diverse data sources can unlock new capabilities in embodied agents, highlighting critical gaps in current methodologies.
Treating tactile signals as active cues rather than passive inputs leads to a dramatic boost in manipulation success rates and accuracy in contact-rich tasks.
VLA models struggle not with *what* they see, but with *how* they see it: FocusVLA reveals that directing attention to task-relevant visual regions unlocks significant performance gains in robotic manipulation.
