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cs.LG2024
Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation
Anh Bui, Long Vuong, Khanh Doan +4
Diffusion models excel at generating visually striking content from text but can inadvertently produce undesirable or harmful content when trained on unfiltered internet data. A pr…
cs.LG2024
Diversity-Aware Agnostic Ensemble of Sharpness Minimizers
Anh Bui, Vy Vo, Tung Pham +2
There has long been plenty of theoretical and empirical evidence supporting the success of ensemble learning. Deep ensembles in particular take advantage of training randomness and…
cs.LG2024★ 1 cited
Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts
Anh Bui, Khanh Doan, Trung Le +3
Diffusion models have demonstrated remarkable capability in generating high-quality visual content from textual descriptions. However, since these models are trained on large-scale…