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CFLoRA: Federated Fine-tuning of LLMs with Complementary Factors for Error-free Aggregation
Federated low-rank adaptation (LoRA) enables collaborative fine-tuning of large language models without centralizing private client data. Its factorized update, however, creates a structural mismatch in federated averaging: averaging the two LoRA factors separately does not equal averaging their pro
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