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cs.LG2025
Flow Map Distillation Without Data
Shangyuan Tong, Nanye Ma, Saining Xie +1
State-of-the-art flow models achieve remarkable quality but require slow, iterative sampling. To accelerate this, flow maps can be distilled from pre-trained teachers, a procedure…
cs.CV2025
Diffusion Transformers with Representation Autoencoders
Boyang Zheng, Nanye Ma, Shengbang Tong +1
Latent generative modeling, where a pretrained autoencoder maps pixels into a latent space for the diffusion process, has become the standard strategy for Diffusion Transformers (D…
cs.CV2025★ 3 cited
Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps
Nanye Ma, Shangyuan Tong, Haolin Jia +8
Generative models have made significant impacts across various domains, largely due to their ability to scale during training by increasing data, computational resources, and model…