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Sparse POT problems can now be solved efficiently with structured regularizers, outperforming entropic methods on cost, sparsity, and speed.
Achieving a 98% reduction in AI traffic without sacrificing performance challenges conventional wisdom about the necessity of precise data representation in VLMs.
Achieving state-of-the-art pose-free novel view synthesis by reusing a single 3D scene across multiple complementary roles transforms how we approach 3D reconstruction and rendering.
