Papers3

#Inception Score

Image Generation with a Sphere Encoder

Kaiyu Yue, Menglin Jia et al.Feb 16arXiv

The Sphere Encoder is a new way to make images fast by teaching an autoencoder to place all images evenly on a big imaginary sphere and then decode random spots on that sphere back into pictures.

#Sphere Encoder#Spherical Latent Space#RMS Normalization

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Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers

Beginner

Yifan Zhou, Zeqi Xiao et al.Dec 18arXiv

This paper introduces Log-linear Sparse Attention (LLSA), a new way for Diffusion Transformers to focus only on the most useful information using a smart, layered search.

#Log-linear Sparse Attention#Hierarchical Top-K#Hierarchical KV Enrichment

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RecTok: Reconstruction Distillation along Rectified Flow

Intermediate

Qingyu Shi, Size Wu et al.Dec 15arXiv

RecTok is a new visual tokenizer that teaches the whole training path of a diffusion model (the forward flow) to be smart about image meaning, not just the starting latent features.

#Rectified Flow#Flow Matching#Visual Tokenizer

Not triaged yet