A Riemannian Geometry for Low-rank Adaptation

Name: A Riemannian Geometry for Low-rank Adaptation
Uploaded: 2026-10-19T13:08:05.867805+00:00
Duration: 795 s
Description: The paper improves Low-rank Adaptation (LoRA) by introducing a custom Riemannian metric for its search space. This metric creates new preconditioning that forces LoRA updates to move closer to full fine-tuning, theoretically ensuring better approximation of the full model's performance and leading to more efficient optimization during training.

The paper improves Low-rank Adaptation (LoRA) by introducing a custom Riemannian metric for its search space. This metric creates new preconditioning that forces LoRA updates to move closer to full fine-tuning, theoretically ensuring better approximation of the full model's performance and leading to more efficient optimization during training.

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