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cs.LG2026
Generalization and Memorization in Rectified Flow
Mingxing Rao, Daniel Moyer
Generative models based on the Flow Matching objective, particularly Rectified Flow, have emerged as a dominant paradigm for efficient, high-fidelity image synthesis. However, whil…
cs.LG2025
Latent Diffusion Inversion Requires Understanding the Latent Space
Mingxing Rao, Bowen Qu, Daniel Moyer
The recovery of training data from generative models ("model inversion") has been extensively studied for diffusion models in the data domain as a memorization/overfitting phenomen…
cs.LG2025
Score-based Membership Inference on Diffusion Models
Mingxing Rao, Bowen Qu, Daniel Moyer
Membership inference attacks (MIAs) against Diffusion Models (DMs) raise pressing privacy concerns by revealing whether a sample was part of the training set. While existing method…