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The hyperbolic Res-MLP (HR-MLP), an architecture extending the attention-free MLP to a non-Euclidean space and enabling direct hyperbolic operations with fewer parameters, facilitating faster training and superior performance compared to Euclidean counterparts is introduced.
Latent diffusion models (LDMs) enable efficient high-resolution image synthesis by denoising in a VAE-compressed latent space. However, fixed visual tokenizers can discard fine textures and structural details, while separate representation and diffusion training creates a mismatch between reconstruction and generation...
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