concept erasure 1inference-time adaptation 1model safety 1multimodal attention 1orthogonal value decomposition 1visual generation 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.CV2026
Uni-AdaVD: Universal Concept Erasure for Visual Generation via Orthogonal Value Decomposition
Qifan Zhou, Yuan Wang, Yanbin Hao +4
The paper introduces Uni-AdaVD, an inference-time framework that removes unwanted concepts from visual generative models by orthogonalizing and shifting value representations, work…
cs.CV2025
Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement Matters
Yuan Wang, Ouxiang Li, Tingting Mu +4
Recent success of text-to-image (T2I) generation and its increasing practical applications, enabled by diffusion models, require urgent consideration of erasing unwanted concepts,…
cs.CV2025
CookingDiffusion: Cooking Procedural Image Generation with Stable Diffusion
Yuan Wang, Bin Zhu, Yanbin Hao +3
Recent advancements in text-to-image generation models have excelled in creating diverse and realistic images. This success extends to food imagery, where various conditional input…