5 papers
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…
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…
Optimization of Module Transferability in Single Image Super-Resolution: Universality Assessment and Cycle Residual Blocks
Haotong Cheng, Zhiqi Zhang, Hao Li +1
Deep learning has substantially advanced the field of Single Image Super-Resolution (SISR). However, existing research has predominantly focused on raw performance gains, with litt…
GraspVLA: a Grasping Foundation Model Pre-trained on Billion-scale Synthetic Action Data
Shengliang Deng, Mi Yan, Songlin Wei +10
Embodied foundation models are gaining increasing attention for their zero-shot generalization, scalability, and adaptability to new tasks through few-shot post-training. However,…