6 papers · 1 filter
FlowErase-OPD: Multi-Concept Erasure via Anchored On-Policy Distillation in Flow Matching Models
Yi Sun, Yimin Zhou, Xinhao Zhong +3
Recent advances in flow matching models have substantially improved the quality of text-to-image generation, but have also raised increasing safety concerns due to their potential…
FlowErase-RL: Rethinking Concept Erasure as Reward Optimization in Flow Matching Models
Yi Sun, Zhiqi Zhang, Xinhao Zhong +5
Recent advances in flow matching models have significantly improved text-to-image generation quality, but also introduce growing safety risks due to the generation of harmful or un…
CPC-VAR:Continual Personalized and Compositional Generation in Visual Autoregressive Models
Junhao Li, Xinhao Zhong, Yi sun +4
Visual autoregressive (VAR) models have recently emerged as an efficient paradigm for text-to-image generation. Despite their strong generative capability, existing VAR-based perso…
ActErase: A Training-Free Paradigm for Precise Concept Erasure via Activation Redirection
Yi Sun, Xinhao Zhong, Hongyan Li +4
Recent advances in text-to-image diffusion models have demonstrated remarkable generation capabilities, yet they raise significant concerns regarding safety, copyright, and ethical…
Differential Vector Erasure: Unified Training-Free Concept Erasure for Flow Matching Models
Zhiqi Zhang, Xinhao Zhong, Yi Sun +4
Text-to-image diffusion models have demonstrated remarkable capabilities in generating high-quality images, yet their tendency to reproduce undesirable concepts, such as NSFW conte…
Closing the Safety Gap: Surgical Concept Erasure in Visual Autoregressive Models
Xinhao Zhong, Yimin Zhou, Zhiqi Zhang +6
The rapid progress of visual autoregressive (VAR) models has brought new opportunities for text-to-image generation, but also heightened safety concerns. Existing concept erasure t…