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arXiv — cs.AI preprintsInternational21 October 2026

Rethinking Cross-Layer Information Routing in Diffusion Transformers

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arXiv:2605.20708v4 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) have become a de facto backbone of modern visual generation, and nearly every major axis of their design -- tokenization, attention, conditioning, objectives, and latent autoencoders -- has been extensively revisited. The residual stream that governs how information accumulates across layers, however, has been directly inherited from the original Transformer. In this paper, we present a systematic empirical analysis of cross-layer information flow in DiTs, jointly along depth and denoising timestep, and ide
— arXiv — cs.AI preprints

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