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cs.LG2024
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Feng Chen +3
Discrete diffusion has emerged as a powerful framework for generative modeling in discrete domains, yet efficiently sampling from these models remains challenging. Existing samplin…
cs.LG2024★ 1 cited
Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning
Daniel Kunin, Allan Raventós, Clémentine Dominé +4
While the impressive performance of modern neural networks is often attributed to their capacity to efficiently extract task-relevant features from data, the mechanisms underlying…