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cs.DC2026
Democratizing LLM Training with the Edge: Challenges, Systems, and the Road Ahead
Ziyue Luo, Jiaxuan Cai, Cedric LeDenmat +27
The growing computational power of modern GPU data centers has let a few industrial giants train and deploy large language models (LLMs) on massive amounts of data. Yet the sheer s…
cs.DC2025
EcoLoRA: Communication-Efficient Federated Fine-Tuning of Large Language Models
Han Liu, Ruoyao Wen, Srijith Nair +6
To address data locality and privacy restrictions, Federated Learning (FL) has recently been adopted to fine-tune large language models (LLMs), enabling improved performance on var…