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RA-VLA transforms robotic adaptation by seamlessly integrating context retrieval with execution, achieving superior performance without the need for training.
A staggering 74% of ball possession sequences in the World Cup failed to create meaningful space, challenging conventional wisdom about possession metrics in football.
Ignoring off-screen players can inflate pitch control errors by over 25 percentage points, but a simple voting mechanism can halve this distortion in live broadcasts.
Achieve ensemble-level sequential recommendation performance with a single network at inference time by distilling diversity from a modular ensemble during training.
Transformer-based models trained directly on high-resolution 7T MRI data can spot MS lesions that classical methods miss, but not without introducing new challenges in boundary variability and artifact-related false positives.
