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Human-robot teams can slash interaction costs by 50% and task times by 25% when robots actively resolve uncertainty about tasks and infer human intent using LLMs and spatial reasoning.
LLMs can orchestrate human input to UAVs, dramatically improving mission success rates while minimizing human interaction.
Diffusion models can learn surprisingly generalizable anatomical representations from unlabeled MRI data, enabling accurate multi-task diagnosis and segmentation across different joints and imaging conditions, even with limited labeled data.
By unifying temporal and visual modalities with fine-grained alignment, VETime leapfrogs existing approaches to achieve state-of-the-art zero-shot time series anomaly detection.
