2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CL2024
YuLan: An Open-source Large Language Model
Yutao Zhu, Kun Zhou, Kelong Mao +35
Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many o…
cs.LG2024★ 2 cited
Federated Learning with Instance-Dependent Noisy Label
Lei Wang, Jieming Bian, Jie Xu
Federated learning (FL) with noisy labels poses a significant challenge. Existing methods designed for handling noisy labels in centralized learning tend to lose their effectivenes…
cs.CR2022★ 2 cited
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy
Wenqiang Ruan, Mingxin Xu, Wenjing Fang +3
Secure multi-party computation-based machine learning, referred to as MPL, has become an important technology to utilize data from multiple parties with privacy preservation. While…