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Low-rank adaptation (LoRA) is one of the most popular task-specific parameter-efficient fine-tuning (PEFT) methods on pre-trained language models for its good performance and computational efficiency.
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Lora: Low-rank adaptation of large language models
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Asymmetry in low-rank adapters of foundation models
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