Papers by Seongbae Lee

1 papers
Riemannian Optimization for LoRA on the Stiefel Manifold (2025.findings-emnlp)

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Challenge: powerful, large language models (LLMs) present significant fine-tuning challenges due to their size.
Approach: They propose to optimize LoRA’s B matrix by imposing explicit orthogonality constraints that achieve near-perfect orthogonal and full effective rank.
Outcome: The proposed method outperforms AdamW and LoRA in terms of parameter efficiency and representational capacity.

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