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20242026
most citedSANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

5 citations · 11 across the 11 of their papers we have counts for

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cs.CV2024★ 5 cited

SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Enze Xie, Junsong Chen, Junyu Chen +8

We introduce Sana, a text-to-image framework that can efficiently generate images up to 40964096 resolution. Sana can synthesize high-resolution, high-quality images with s…

cs.CV2024★ 1 cited

HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Haotian Tang, Yecheng Wu, Shang Yang +7

We introduce Hybrid Autoregressive Transformer (HART), an autoregressive (AR) visual generation model capable of directly generating 1024x1024 images, rivaling diffusion models in…

cs.LG2024

COAT: Compressing Optimizer states and Activation for Memory-Efficient FP8 Training

Haocheng Xi, Han Cai, Ligeng Zhu +4

FP8 training has emerged as a promising method for improving training efficiency. Existing frameworks accelerate training by applying FP8 computation to linear layers while leaving…

cs.CV2024★ 2 cited

Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

Junyu Chen, Han Cai, Junsong Chen +6

We present Deep Compression Autoencoder (DC-AE), a new family of autoencoder models for accelerating high-resolution diffusion models. Existing autoencoder models have demonstrated…

cs.LG2024★ 1 cited

Wolf: Dense Video Captioning with a World Summarization Framework

Boyi Li, Ligeng Zhu, Ran Tian +20

We propose Wolf, a WOrLd summarization Framework for accurate video captioning. Wolf is an automated captioning framework that adopts a mixture-of-experts approach, leveraging comp…