1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Can Federated Learning Safeguard Private Data in LLM Training? Vulnerabilities, Attacks, and Defense Evaluation
Wenkai Guo, Xuefeng Liu, Haolin Wang +3
Fine-tuning large language models (LLMs) with local data is a widely adopted approach for organizations seeking to adapt LLMs to their specific domains. Given the shared characteri…
cs.LG2024★ 1 cited
Why Go Full? Elevating Federated Learning Through Partial Network Updates
Haolin Wang, Xuefeng Liu, Jianwei Niu +2
Federated learning is a distributed machine learning paradigm designed to protect user data privacy, which has been successfully implemented across various scenarios. In traditiona…