Mitigating Sequential Reappearance in Diffusion Data-Point Unlearning

arXiv:2609.25166 · cs.LG, cs.AI · Submitted 2026-09-21 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-21

Updated: 2026-09-21

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 30× in this paper · explained in 8 episodes
• Diffusion Models — 27× in this paper · explained in 6 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Generalization — 6× in this paper · explained in 13 episodes
• Computational overhead — 5× in this paper · explained in 2 episodes
• Machine Unlearning — 4× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 3× in this paper
• Computer Vision and Pattern Recognition — 3× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• AUC — 2× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Adversarial Examples — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Adversarial Training — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Unlearning the Unpromptable: Prompt-free Instance Unlearning in Diffusion Models
• Sharpness-Aware Parameter Selection for Machine Unlearning
• Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion
• A Reproducible Extraction of Training Images from Diffusion Models

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