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Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning

Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning

29 November 2024
Kaustubh Ponkshe
Raghav Singhal
Eduard A. Gorbunov
Alexey Tumanov
Samuel Horváth
Praneeth Vepakomma
ArXivPDFHTML

Papers citing "Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning"

2 / 2 papers shown
Title
AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections
AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections
Xin Yu
Yujia Wang
Jinghui Chen
Lingzhou Xue
17
0
0
18 May 2025
Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning
Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning
Raghav Singhal
Kaustubh Ponkshe
Rohit Vartak
Lav R. Varshney
Praneeth Vepakomma
FedML
79
0
0
24 Feb 2025
1