Understanding diffusion models requires rethinking (again) generalization

ArXi:2605.06077v1 Announce Type: new This position paper argues that understanding generalization in diffusion models requires fundamentally new theoretical frameworks that go beyond both classical statistical learning theory and the benign overfitting paradigm developed for supervised learning. In diffusion models, unlike in supervised learning, memorization of