arXiv:2607. 24101v1 Announce Type: cross Abstract: Concept unlearning is increasingly used to limit the reproduction of protected or unsafe visual concepts in text-to-image models.
By Keyu Li, Jin Gao, Jialing Zhang, Dequan Wang
arXiv:2609.37127v1 Announce Type: new
Abstract: Establishing unbranding as a critical practice to prevent visual logos from acquiring negative connotations is standard in image generation. Large Lang...
By Kajetan O\.z\'og, Alicja Wojciechowska, Dawid Malarz, Pawe{\l} Batorski, Artur Kasymov, Przemys{\l}aw Spurek
arXiv:2609.01433v1 Announce Type: new
Abstract: Concept erasure aims to suppress unsafe, privacy-sensitive, or undesirable generations in text-to-image diffusion models while preserving benign semant...
By Qinghui Gong, Xunlei Chen, Yu-Xuan Zhang, Hua Meng, Zhengchun Zhou
arXiv:2610.20603v1 Announce Type: new
Abstract: We present CommerceGen-Studio, an end-to-end framework for generating commercial-grade main images for e-commerce Stock Keeping Units (SKUs). Our frame...
By Xiaoli Xu, Zhengtao Wu, Zhengze Xu, Tao Liu, Yongchao Du, Zuan Gao, Xingjian Wang, Hao Yan, Mengting Chen, Wei Li, Bo Zheng
We present CommerceGen-Studio, an end-to-end framework for generating commercial-grade main images for e-commerce Stock Keeping Units (SKUs). Our framework is organized along a three-stage pipeline of...
arXiv:2412.07658v3 Announce Type: replace-cross
Abstract: Text-to-image diffusion models have rapidly transitioned from research prototypes to widely deployed tools. Along with their impressive capab...
By Anubhav Jain, Takashi Shibuya, Yuya Kobayashi, Yuhta Takida, Nasir Memon, Julian Togelius, Yuki Mitsufuji