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ReaDiT Guidance: Control for Image and Video Generation using Diffusion Transformer Features

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

We present DiT Readout (ReaDiT) Guidance, a lightweight framework for controlling generation with Diffusion Transformer (DiT) models via their internal feature representations. ReaDiT Guidance uses features from a single DiT block to steer the generative process according to spatial targets - like depth, pose, or edge maps - provided at test time. Furthermore, since modern text-to-video models are largely built on DiT backbones, ReaDiT Guidance naturally extends to video generation, enabling camera and motion control. Experimental results demonstrate that our approach achieves competitive or i

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First collected: 2026-09-20T22:31:48.298Z. This is not the publication date.