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#artificial intelligence Preprint Sep 2026

D-Scope: Decomposing and Steering Diffusion Transformers with Sparse Autoencoders

Sparse autoencoders (SAEs) reveal visual structure in diffusion transformers (DiTs), but interpreting a feature does not establish whether it can be used to control generation. We introduce D-Scope (Diffusion Scope), a framework that connects feature interpretation to generation control through shared visual evidence....

Xinyue Xu, Jiahao Zhang, Li-Jie Hu et al. · 1 citation
#machine learning Preprint Sep 2026

GPARA: Graph-Posterior-Aligned Refinement and Active Acquisition for Grounding Diffusion Priors

Active grounding of a frozen diffusion prior requires jointly determining where new measurements should be taken and how they should be used to refine the current reconstruction. Posterior-ensemble-based methods can estimate acquisition utility from generated samples, but require repeated ensemble generation as observa...

Wang-Qian Chen, Hao Wang, Yu-Meng Zhang et al. · 0 citations

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