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CrossFlow Model Generates Across Latent and Pixel Spaces

Modernity/arxiv 2h2h Impact 7
A new model named CrossFlow has been developed for one-step generation across latent and pixel spaces. Most diffusion and flow-matching generators define the prior, probability path, and prediction target.

Topics

generative AI machine learning computer vision

Developing

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Sources · 7 independent

Modernity/arxiv

“CrossFlow: One-Step Generation Across Latent and Pixel Spaces. Authors: Xiyuan Wang, Xiao Zhang, Yang Li, Ruoxi Jiang, Zhao Zhong, Liefeng Bo, Muhan Zhang Abstract: Most diffusion and flow-matching generators define the prior, probability path, and prediction ta”

Modernity/arxiv

“Sun, Tingting Yang, Liwen Jing, Yuxuan Shi, Maged Elkashlan, Mérouane Debbah Abstract: Wireless foundation models (WFMs) have recently emerged as a promising paradigm for AI-n...”

Modernity/arxiv

“Xinyi Wang, Sihang Jiang, Han Xia, Zhaoqian Dai, Shuguang Ma, Fei Yu, Jiaqing Liang and 1 others Abstract: Large reasoning models rely on long chain-of-...”

Radio 4

“The CrossFlow model generates across latent and pixel spaces.”

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