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End-to-end driving models are surprisingly bad at using navigation, but a new framework shows how to inject it for SOTA results.
Humanoid robots can now traverse steps up to 20cm and gaps up to 80cm thanks to a contrastive learning approach that forces MoE experts to specialize on different terrain types.
