Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly

arXiv:2310.03150v2 Announce Type: replace
Abstract: Large Language Models (LLM) and foundation models are popular as they offer new opportunities for individuals and businesses to improve natural language processing, interact with data, and retrieve information faster. However, training or fine-tuning LLMs requires a vast amount of data, which can be challenging to access due to legal or technical restrictions and may require private computing resources. Federated Learning (FL) is a solution designed to overcome these challenges and expand data access for …

abstract arxiv businesses cs.dc cs.lg cs.pf data edge faster fine-tuning foundation good however information language language models language processing large language large language models llm llms natural natural language natural language processing opportunities popular processing training type vast