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VLMs can be taught to *use* latent geometry by training them to read continuous geometric tokens, rather than just reconstructing geometry from RGB.
A massive 2.6M-scene benchmark and a novel generative model finally unlock robust dexterous grasping in cluttered environments, outperforming prior methods without post-optimization.
Robots can learn contact-rich dexterity directly from human skin: co-training on aligned human visual-tactile-action data more than doubles real-world manipulation success (70% vs. 29%) with zero performance saturation up to 1,000 demonstrations.
Adversarial clothing can successfully evade thermal person detectors with over 80% effectiveness, exposing critical security flaws in AI-driven surveillance systems.
DreamHand achieves a groundbreaking 40% reduction in error for 3D hand trajectory recovery in occluded environments, setting a new standard for egocentric video analysis.