Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders
arXiv:2602.10099v2 Announce Type: replace-cross Abstract: Leveraging representation encoders for generative modeling offers a path for efficient, high-fidelity synthesis. However, standard diffusion t