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Training robots in a photorealistic Gaussian Splatting simulator transfers surprisingly well to the real world, boosting scene understanding and navigation performance.
A single spatial token, learned via occupancy prediction on a massive dataset, is surprisingly effective at injecting crucial spatial awareness into vision-language navigation, leading to state-of-the-art performance.
