GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning

NeurIPSSpotlight2025

Authors
Yeonjoon Jung, Daehyun Ahn, Hyungjun Kim, Taesu Kim, Eunhyeok Park
Venue
NeurIPS 2025
Track
Spotlight

TL;DR

Low-Rank Adaptation (LoRA) is a popular method for parameter-efficient fine-tuning (PEFT) of generative models, valued for its simplicity and effectiveness…

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Topics

generative model fine-tuning efficient

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