no code implementations • 20 Feb 2024 • Yujun Zhou, Yufei Han, Haomin Zhuang, Taicheng Guo, Kehan Guo, Zhenwen Liang, Hongyan Bao, Xiangliang Zhang
Large Language Models (LLMs) demonstrate remarkable capabilities across diverse applications.
no code implementations • 8 Aug 2023 • Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan
Federated learning (FL) has been widely deployed to enable machine learning training on sensitive data across distributed devices.
1 code implementation • 18 Apr 2023 • Zhaoming Kong, Fangxi Deng, Haomin Zhuang, Jun Yu, Lifang He, Xiaowei Yang
In this paper, to investigate the applicability of existing denoising techniques, we compare a variety of denoising methods on both synthetic and real-world datasets for different applications.
1 code implementation • 29 Mar 2023 • Haomin Zhuang, Yihua Zhang, Sijia Liu
In this work, we study the problem of adversarial attack generation for Stable Diffusion and ask if an adversarial text prompt can be obtained even in the absence of end-to-end model queries.