AI RESEARCH
A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations
arXiv CS.LG
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ArXi:2604.24468v1 Announce Type: cross Fine-tuning unlocks large language models (LLMs) for specialized applications, but its high computational cost often puts it out of reach for resource-constrained organizations. While cloud platforms could provide the needed resources, data privacy concerns make sharing sensitive information with third parties risky. A promising solution is split learning for LLM fine-tuning, which divides the model between clients and a server, allowing collaborative and secure.