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Spatially consistent language embeddings can drastically improve robotic task performance, making ReSiReg a game-changer for real-world applications.
Achieving 95.4% convergence under perturbation, ART-VS outperforms traditional methods by adapting resolution dynamically, leading to a 53% reduction in positioning error.
