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Lazy second-order optimization is far more efficient than previously thought, with a new bound achieving near-optimality.
Operating a photonic chip at the edge of driven-dissipative criticality yields 95.2% classification accuracy with just 44 parameters while surviving extreme noise down to -30 dB.
Achieve SOTA medical image segmentation with barely any labels by combining fine-grained visual features with text-based semantic guidance.
Achieve superior scene-consistent video generation by training a model to iteratively estimate geometry and render novel views, using geometry as context.