David Ahmedt-Aristizabal

Probing Diffusion Denoising Dynamics for Contrastive Representation Learning

D$^3CL is established as a parameter-efficient adaptation framework for pretrained diffusion models, showing that noise-level contrastive learning can structure denoising representations for discriminative tasks while maintaining generative performance.