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CANS slashes inference latency by up to 50% in collaborative edge computing by enabling devices to learn optimal DNN partitions through shared feedback.
A new 3D representation and BEV alignment framework drastically enhance the generalization of robotic manipulation policies across varied environments and robot types.
