Bi-Erasing: A Bidirectional Framework for Concept Removal in Diffusion Models

• URL: http://arxiv.org/abs/2512.13039v2
• Date: Tue, 16 Dec 2025 09:24:35 GMT
• Title: Bi-Erasing: A Bidirectional Framework for Concept Removal in Diffusion Models
• Authors: Hao Chen, Yiwei Wang, Songze Li,
• Abstract summary: Concept erasure has become a mainstream approach to mitigating unsafe or illegal image generation in text-to-image models.<n>We propose a novel Bidirectional Image-Guided Concept Erasure (Bi-Erasing) framework that performs concept suppression and safety enhancement simultaneously.
• Score: 32.35244979539898
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Concept erasure, which fine-tunes diffusion models to remove undesired or harmful visual concepts, has become a mainstream approach to mitigating unsafe or illegal image generation in text-to-image models.However, existing removal methods typically adopt a unidirectional erasure strategy by either suppressing the target concept or reinforcing safe alternatives, making it difficult to achieve a balanced trade-off between concept removal and generation quality. To address this limitation, we propose a novel Bidirectional Image-Guided Concept Erasure (Bi-Erasing) framework that performs concept suppression and safety enhancement simultaneously. Specifically, based on the joint representation of text prompts and corresponding images, Bi-Erasing introduces two decoupled image branches: a negative branch responsible for suppressing harmful semantics and a positive branch providing visual guidance for safe alternatives. By jointly optimizing these complementary directions, our approach achieves a balance between erasure efficacy and generation usability. In addition, we apply mask-based filtering to the image branches to prevent interference from irrelevant content during the erasure process. Across extensive experiment evaluations, the proposed Bi-Erasing outperforms baseline methods in balancing concept removal effectiveness and visual fidelity.

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