Spatial Gram Alignment aligns internal self-similarities of LDM features with foundation priors to reconcile global structure and fine details in ultra-high-resolution text-to-image synthesis.
GANs trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30
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DiRotQ uses PCA-based rotation-aware activation quantization combined with GPTQ to achieve better FID and PSNR in 4-bit diffusion transformers than prior methods like SVDQuant.
A latent diffusion model jointly synthesizes MRI volumes and mixed-type tabular clinical data in a shared space via cross-attention and separate decoders after VAE fusion.
citing papers explorer
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Spatial Gram Alignment for Ultra-High-Resolution Image Synthesis
Spatial Gram Alignment aligns internal self-similarities of LDM features with foundation priors to reconcile global structure and fine details in ultra-high-resolution text-to-image synthesis.
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DiRotQ: Rotation-Aware Quantization for 4-bit Diffusion Transformers
DiRotQ uses PCA-based rotation-aware activation quantization combined with GPTQ to achieve better FID and PSNR in 4-bit diffusion transformers than prior methods like SVDQuant.
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Multimodal synthesis of MRI and tabular data with diffusion in a joint latent space via cross-attention
A latent diffusion model jointly synthesizes MRI volumes and mixed-type tabular clinical data in a shared space via cross-attention and separate decoders after VAE fusion.