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cs.LG2026
Ambient Dataloops: Generative Models for Dataset Refinement
Adrián Rodríguez-Muñoz, William Daspit, Adam Klivans +3
We propose Ambient Dataloops, an iterative framework for refining datasets that makes it easier for diffusion models to learn the underlying data distribution. Modern datasets cont…
cs.LG2024
Characterizing Model Robustness via Natural Input Gradients
Adrián Rodríguez-Muñoz, Tongzhou Wang, Antonio Torralba
Adversarially robust models are locally smooth around each data sample so that small perturbations cannot drastically change model outputs. In modern systems, such smoothness is us…