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By predicting latent features instead of pixels, PROSPECT achieves state-of-the-art VLN performance and long-horizon robustness without adding inference overhead.
By aligning latent representations with multiple visual foundation models, FRAPPE offers a more scalable and data-efficient way to imbue generalist robotic policies with robust world-awareness.