EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action
EWAM is a unified embodied model that learns to perform actions by dynamically specializing its internal processing layers. It achieves this through asymmetric joint attention, causing the model to shift focus from understanding semantics early on, to predicting future visuals in the middle, and finally refining precise motor commands for execution.