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Pairing learned generative transport with theoretically prescribed normal contraction eliminates off-manifold drift down to $10^{-7}$ precision, driving double-digit success gains in robotic manipulation.
Tensegrity robots can morph into task-specific configurations, revolutionizing cooperative robotic behaviors in dynamic environments.
LLM-powered autonomous hacking frameworks often hallucinate attacks rather than execute them, revealing a critical gap between theoretical potential and real-world effectiveness.
