RidgeLoRA: Matrix Ridge Enhanced Low-Rank Adaptation of Large Language Models

NeurIPSSpotlight2025

Authors
Junda Zhu, Jun Ai, Yujun Li, Yichun Yin, Yasheng Wang, Lifeng Shang, Qun Liu
Venue
NeurIPS 2025
Track
Spotlight

TL;DR

As one of the state-of-the-art parameter-efficient fine-tuning~(PEFT) methods, Low-Rank Adaptation (LoRA) enables model optimization with reduced computational cost through trainable low-rank matrix…

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Topics

large language model language model optimization fine-tuning efficient

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