4 papers
Variational Masked Diffusion Models
Yichi Zhang, Alex Schwing, Zhizhen Zhao
Masked diffusion models have recently emerged as a flexible framework for discrete generative modeling. However, a key limitation of standard masked diffusion is its inability to e…
Hierarchical Rectified Flow Matching with Mini-Batch Couplings
Yichi Zhang, Yici Yan, Alex Schwing +1
Flow matching has emerged as a compelling generative modeling approach that is widely used across domains. To generate data via a flow matching model, an ordinary differential equa…
DiT-Air: Revisiting the Efficiency of Diffusion Model Architecture Design in Text to Image Generation
Chen Chen, Rui Qian, Wenze Hu +8
In this work, we empirically study Diffusion Transformers (DiTs) for text-to-image generation, focusing on architectural choices, text-conditioning strategies, and training protoco…
Towards Hierarchical Rectified Flow
Yichi Zhang, Yici Yan, Alex Schwing +1
We formulate a hierarchical rectified flow to model data distributions. It hierarchically couples multiple ordinary differential equations (ODEs) and defines a time-differentiable…