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most citedInference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

3 citations · 6 across the 8 of their papers we have counts for

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cs.CV2024★ 3 cited

SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Nanye Ma, Mark Goldstein, Michael S. Albergo +3

We present Scalable Interpolant Transformers (SiT), a family of generative models built on the backbone of Diffusion Transformers (DiT). The interpolant framework, which allows for…