2 papers
cs.AI2024
Safety Alignment Backfires: Preventing the Re-emergence of Suppressed Concepts in Fine-tuned Text-to-Image Diffusion Models
Sanghyun Kim, Moonseok Choi, Jinwoo Shin +1
Fine-tuning text-to-image diffusion models is widely used for personalization and adaptation for new domains. In this paper, we identify a critical vulnerability of fine-tuning: sa…
cs.CV2024
Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion
Sanghyun Kim, Seohyeon Jung, Balhae Kim +3
This paper addresses the societal concerns arising from large-scale text-to-image diffusion models for generating potentially harmful or copyrighted content. Existing models rely h…