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News/Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence
arxiv
PublishedJune 1, 2026 at 4:00 AM

Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence

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arXiv:2605.31484v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is the most widely adopted method for fine-tuning large language models. Notably, LoRA is inherently overparameterized: multiple pairs of low-rank factors can yield the same adapted weight matrix. We show--both theoretically

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