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CrossMean is introduced, which replaces this matrix on one side with a bilinear statistic that pairs merged and expert activations, and a label-free criterion is derived that indicates the task sets in which accounting for the merged activations improves the merge more.
MS-Flow, which represents the trajectory as a sequence of intermediate latent states rather than a single initial code, is proposed, which represents the trajectory as a sequence of intermediate latent states rather than a single initial code and reduces memory consumption while improving reconstruction quality.
Graph Transformers produce, for each attention head, a dense $n\times n$ matrix of learned pairwise interactions. We ask a fundamental question: do these attention-induced graphs converge to a stable limit object as $n$ grows, or does the learned interaction pattern remain unstructured and size-dependent? We answer thi...
GeoCFM is introduced, a conditional flow-matching model that generates mineral occurrence point sets conditioned on multi-channel geo-images that improves geometric agreement with observed occurrences over score-map and non-conditional baselines, while representing epistemic uncertainty through conditional sampling.
This work explores image generation using flow matching using flow matching and proposes an iterative process that can be integrated into virtually any generative modeling technique, thereby enhancing the performance and robustness of image synthesis systems.
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