AI RESEARCH
Two Stage Wireless Federated LoRA Fine-Tuning with Sparsified Orthogonal Updates
arXiv CS.LG
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ArXi:2505.00333v2 Announce Type: replace Transformer-based large language models (LLMs) have achieved remarkable success across various tasks. Yet, fine-tuning such massive models in federated learning (FL) settings poses significant challenges due to resource constraints and communication overhead. Low-Rank Adaptation (LoRA) addresses these issues by