Seongbae Lee

Riemannian Optimization for LoRA on the Stiefel Manifold

While powerful, large language models (LLMs) present significant fine-tuning challenges due to their size. Parameter-efficient fine-tuning (PEFT) methods like LoRA provide solutions, yet suffer from critical optimizer inefficiencies; notably basis redundancy in LoRA’s B matrix when using AdamW, whic