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A single machine-learned potential accurately models copper-carbon interactions from equilibrium to extreme non-equilibrium conditions, enabling large-scale simulations for diverse applications.
Bridging the perception-reasoning gap in visual planning, MGSD boosts model performance by over 19% while relying solely on visual inference during deployment.
Achieve real-time, globally consistent, and photorealistic SLAM in large-scale environments by directly performing loop closure on optimized Gaussian maps.
