No Concept Escapes the Audit: Auditing-Aware Unlearning for Verifiable Concept Erasure in Diffusion Models

arXiv:2610.05401 · cs.LG, cs.AI · Submitted 2026-10-04 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-10-04

Updated: 2026-10-11

Code: https://github.com/fastai/imagenette

Terminology

• Diffusion Model — 1× in this paper · explained in 9 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes

Sources

• The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
• Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them
• ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning
• Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts
• Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models
• SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
• Certified Data Removal from Machine Learning Models
• Knowledge Unlearning for Mitigating Privacy Risks in Language Models
• Diffusion Models for Medical Image Analysis: A Comprehensive Survey
• One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework
• AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models
• Position: Bridge the Gaps between Machine Unlearning and AI Regulation
• A Survey of Machine Unlearning
• GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
• Circumventing Concept Erasure Methods For Text-to-Image Generative Models
• SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
• Unlearning or Concealment? A Critical Analysis and Evaluation Metrics for Unlearning in Diffusion Models
• Ring-A-Bell! How Reliable are Concept Removal Methods for Diffusion Models?
• CE-SDWV: Effective and Efficient Concept Erasure for Text-to-Image Diffusion Models via a Semantic-Driven Word Vocabulary
• Machine Unlearning: A Comprehensive Survey

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