Federated Fine-Tuning of Foundation Models (Fed-LLMs): Parameter-Efficient Adapters, Split Learning, and Gradient Privacy Bounds
Abstract—Fine-tuning Large Language Models (LLMs) and Vision Foundation Models on private, decentralized domain data is essential for specialized healthcare, legal, and financial enterprise applications. However, centralizing domain-specific text corpora triggers catastrophic data privacy violations under stringent reg...
Rohit Kumar, Inderkumawat, Vishal Shrivastava et al.
· Zenodo (CERN European Organi... · 0 citations