Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves
Published in arXiv preprint arXiv:2512.00242, 2025
ArXiv preprint on Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves.
Published in arXiv preprint arXiv:2512.00242, 2025
ArXiv preprint on Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves.
Published in CVPR (Computer Vision and Pattern Recognition) 2025 Workshops (Nashville, USA ๐บ๐ธ), 2025
Z-SASLM introduces a zero-shot, fine-tuning-free approach to style alignment in diffusion models by blending multiple reference styles directly in latent space using spherical linear interpolation (SLI) with learned, context-aware weights. The method avoids model retraining, preserves content semantics, and yields consistent style transfer across prompts and seeds.