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LoRA-GA$^2$: Low Rank Adaptation with Multi-step Gradient Adaptive Alignment
Low-Rank Adaptation (LoRA) is a prominent fine-tuning method for large models, achieving competitive performance with reduced memory overhead. However, a persistent performance gap remains between LoRA and full fine-tuning. Recent studies have sought to narrow this gap by employing one-step gradient
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