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cs.CV2025★ 1 cited
Mitigating Sexual Content Generation via Embedding Distortion in Text-conditioned Diffusion Models
Jaesin Ahn, Heechul Jung
Diffusion models show remarkable image generation performance following text prompts, but risk generating sexual contents. Existing approaches, such as prompt filtering, concept re…
cs.CV2021★ 2 cited
Rethinking Query, Key, and Value Embedding in Vision Transformer under Tiny Model Constraints
Jaesin Ahn, Jiuk Hong, Jeongwoo Ju +1
A vision transformer (ViT) is the dominant model in the computer vision field. Despite numerous studies that mainly focus on dealing with inductive bias and complexity, there remai…