Replication in visual diffusion models: A survey and outlook

W Wang, Y Sun, Z Yang, Z Hu, Z Tan… - arXiv preprint arXiv …, 2024 - arxiv.org
Visual diffusion models have revolutionized the field of creative AI, producing high-quality
and diverse content. However, they inevitably memorize training images or videos …

A geometric framework for understanding memorization in generative models

BL Ross, H Kamkari, Z Liu, T Wu, G Stein… - ICML 2024 Workshop …, 2024 - openreview.net
As deep generative models have progressed, recent work has shown that they are capable
of memorizing and reproducing training datapoints when deployed. These findings call into …

Towards a Theoretical Understanding of Memorization in Diffusion Models

Y Chen, X Ma, D Zou, YG Jiang - arXiv preprint arXiv:2410.02467, 2024 - arxiv.org
As diffusion probabilistic models (DPMs) are being employed as mainstream models for
Generative Artificial Intelligence (GenAI), the study of their memorization of training data has …

SolidMark: Evaluating Image Memorization in Generative Models

N Kriplani, M Pham, G Somepalli, C Hegde… - Neurips Safe Generative … - openreview.net
Recent works have shown that diffusion models are able to memorize training images and
emit them at generation time. However, the metrics used to evaluate memorization and its …