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SpectralDiT: Timestep-Conditioned Spectral Residual Correction for Flow-Matching DiTs
[Submitted on 17 Jun 2026] · 2026-06-18 · via cs updates on arXiv.org

Computer Science > Computer Vision and Pattern Recognition

arXiv:2606.18765 (cs)

[Submitted on 17 Jun 2026]

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Abstract:We propose SpectralDiT, a lightweight modification to flow-matching Diffusion Transformers that adds timestep-conditioned spectral correction to the MLP residual branch. The module decomposes each residual update into low- and high-frequency components on the patch-token grid, then learns a zero-initialized additive gate so the model initially matches the baseline DiT. On CIFAR-10 pixel-space generation, SpectralDiT improves FID from 20.78 to 19.71 at patch size 1 and reduces the radial Fourier spectrum gap. Furthermore, we scale our method to latent diffusion on ImageNet-100. With 0.6% additional theoretical FLOPs and 1.36% additional parameters, SpectralDiT improves latent flow-matching, achieving an 8.7% relative FID reduction under classifier-free guidance (CFG 2.0). All reported results are averaged over five seeds. Ablations and gate visualizations on CIFAR-10 reveal stable block-specific spectral correction patterns.

Submission history

From: Jiayu Tian [view email]
[v1] Wed, 17 Jun 2026 07:25:24 UTC (479 KB)

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