[2603.25758] A-SelecT: Automatic Timestep Selection for Diffusion Transformer Representation Learning

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.25758 (cs) [Submitted on 25 Mar 2026] Title:A-SelecT: Automatic Timestep Selection for Diffusion Transformer Representation Learning Authors:Changyu Liu, James Chenhao Liang, Wenhao Yang, Yiming Cui, Jinghao Yang, Tianyang Wang, Qifan Wang, Dongfang Liu, Cheng Han View a PDF of the paper titled A-SelecT: Automatic Timestep Selection for Diffusion Transformer Representation Learning, by Changyu Liu and 8 other authors View PDF HTML (experimental) Abstract:Diffusion models have significantly reshaped the field of generative artificial intelligence and are now increasingly explored for their capacity in discriminative representation learning. Diffusion Transformer (DiT) has recently gained attention as a promising alternative to conventional U-Net-based diffusion models, demonstrating a promising avenue for downstream discriminative tasks via generative pre-training. However, its current training efficiency and representational capacity remain largely constrained due to the inadequate timestep searching and insufficient exploitation of DiT-specific feature representations. In light of this view, we introduce Automatically Selected Timestep (A-SelecT) that dynamically pinpoints DiT's most information-rich timestep from the selected transformer feature in a single run, eliminating the need for both computationally intensive exhaustive timestep searching and suboptimal discriminative feature selection. Extensi...