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Semantic acceptance rates can be misleading, with up to 44.2% of models failing to prevent observable harm even when they pass initial checks.
GRAIL achieves an impressive 84% success rate in real-world object pick-up tasks using only synthetic data, revolutionizing humanoid robot training.
