When Are Concepts Erased From Diffusion Models?

• URL: http://arxiv.org/abs/2505.17013v4
• Date: Fri, 30 May 2025 06:00:33 GMT
• Title: When Are Concepts Erased From Diffusion Models?
• Authors: Kevin Lu, Nicky Kriplani, Rohit Gandikota, Minh Pham, David Bau, Chinmay Hegde, Niv Cohen,
• Abstract summary: Concept erasure is the ability to selectively prevent a model from generating specific concepts.<n>We propose two conceptual models for the erasure mechanism in diffusion models.<n>To thoroughly assess whether a concept has been truly erased from the model, we introduce a suite of independent evaluations.
• Score: 44.89615668122767
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Concept erasure, the ability to selectively prevent a model from generating specific concepts, has attracted growing interest, with various approaches emerging to address the challenge. However, it remains unclear how thoroughly these methods erase the target concept. We begin by proposing two conceptual models for the erasure mechanism in diffusion models: (i) reducing the likelihood of generating the target concept, and (ii) interfering with the model's internal guidance mechanisms. To thoroughly assess whether a concept has been truly erased from the model, we introduce a suite of independent evaluations. Our evaluation framework includes adversarial attacks, novel probing techniques, and analysis of the model's alternative generations in place of the erased concept. Our results shed light on the tension between minimizing side effects and maintaining robustness to adversarial prompts. Broadly, our work underlines the importance of comprehensive evaluation for erasure in diffusion models.

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