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Task-conditioned foveated perception can drastically enhance the robustness and efficiency of robotic foundation models by aligning policy learning with relevant visual evidence.
Generating missing multi-view data from diverse driving videos boosts closed-loop driving robustness in edge cases by over 30%.
UniTac achieves state-of-the-art tactile understanding and generation by seamlessly integrating sensor and object attributes, revolutionizing how we interpret touch across modalities.
Current AI agents excel in structured tasks but falter at generating novel insights and tackling open-ended scientific challenges.
