3 papers
cs.CV2026
Erasing Thousands of Concepts: Towards Scalable and Practical Concept Erasure for Text-to-Image Diffusion Models
Hoigi Seo, Byung Hyun Lee, Jaehyun Cho +2
Large-scale text-to-image (T2I) diffusion models deliver remarkable visual fidelity but pose safety risks due to their capacity to reproduce undesirable content, such as copyrighte…
cs.CV2025
Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank Adaptation
Byung Hyun Lee, Sungjin Lim, Se Young Chun
Fine-tuning based concept erasing has demonstrated promising results in preventing generation of harmful contents from text-to-image diffusion models by removing target concepts wh…
cs.CV2025
Concept Pinpoint Eraser for Text-to-image Diffusion Models via Residual Attention Gate
Byung Hyun Lee, Sungjin Lim, Seunggyu Lee +2
Remarkable progress in text-to-image diffusion models has brought a major concern about potentially generating images on inappropriate or trademarked concepts. Concept erasing has…