27 citations · 28 across the 3 of their papers we have counts for
3 papers
cs.CV2025
FNBench: Benchmarking Robust Federated Learning against Noisy Labels
Xuefeng Jiang, Jia Li, Nannan Wu +7
Robustness to label noise within data is a significant challenge in federated learning (FL). From the data-centric perspective, the data quality of distributed datasets can not be…
cs.CL2025★ 1 cited
Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study
Xuefeng Jiang, Lvhua Wu, Sheng Sun +5
Code vulnerability detection (CVD) is essential for addressing and preventing system security issues, playing a crucial role in ensuring software security. Previous learning-based…
cs.LG2024★ 27 cited
Tackling Noisy Clients in Federated Learning with End-to-end Label Correction
Xuefeng Jiang, Sheng Sun, Jia Li +6
Recently, federated learning (FL) has achieved wide successes for diverse privacy-sensitive applications without sacrificing the sensitive private information of clients. However,…