2 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CR2024★ 2 cited
LLM-PBE: Assessing Data Privacy in Large Language Models
Qinbin Li, Junyuan Hong, Chulin Xie +10
Large Language Models (LLMs) have become integral to numerous domains, significantly advancing applications in data management, mining, and analysis. Their profound capabilities in…
cs.LG2023★ 1 cited
Exploiting Label Skews in Federated Learning with Model Concatenation
Yiqun Diao, Qinbin Li, Bingsheng He
Federated Learning (FL) has emerged as a promising solution to perform deep learning on different data owners without exchanging raw data. However, non-IID data has been a key chal…
cs.LG2023★ 2 cited
Effective and Efficient Federated Tree Learning on Hybrid Data
Qinbin Li, Chulin Xie, Xiaojun Xu +5
Federated learning has emerged as a promising distributed learning paradigm that facilitates collaborative learning among multiple parties without transferring raw data. However, m…