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Multi-robot navigation policies can now dynamically adjust risk sensitivity by explicitly forecasting occupancy uncertainty across agents, dramatically improving safety in unseen environments.
Explicitly managing safety and proximity in human-following tasks leads to a superior balance that outperforms conventional RL approaches, even in unpredictable environments.
Hallucination rates drop to just 8.1% with TAVR-VLM, revolutionizing the reliability of AI-generated surgical reports.