LoRA-FA: Memory-efficient Low-rank Adaptation for Large Language Models Fine-tuning
Paper • 2308.03303 • Published • 3 •
2
Benjamin Bossan
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commentedon a paper 4 days ago
LoRA-FA: Memory-efficient Low-rank Adaptation for Large Language Models
Fine-tuning commentedon a paper 4 days ago
LoRA+: Efficient Low Rank Adaptation of Large Models commentedon a paper 4 days ago
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token ProjectionsOrganizations
commented 20
papers 4 days ago
LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 7 •
3
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
Paper • 2405.17991 • Published • 14 •
5
Robust and Efficient Fine-tuning of LLMs with Bayesian Reparameterization of Low-Rank Adaptation
Paper • 2411.04358 • Published •
1
Block-Diagonal LoRA for Eliminating Communication Overhead in Tensor Parallel LoRA Serving
Paper • 2510.23346 • Published •
1
LoRA-GA: Low-Rank Adaptation with Gradient Approximation
Paper • 2407.05000 • Published •
1
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Paper • 2310.08659 • Published • 30 •
5
A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA
Paper • 2312.03732 • Published • 12 •
1
OLoRA: Orthonormal Low-Rank Adaptation of Large Language Models
Paper • 2406.01775 • Published • 3 •
1
CorDA: Context-Oriented Decomposition Adaptation of Large Language Models
Paper • 2406.05223 • Published • 4 •
1
PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models
Paper • 2404.02948 • Published • 4 •
1
X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Design
Paper • 2402.07148 • Published • 6 •
1
Exploring Sparsity for Parameter Efficient Fine Tuning Using Wavelets
Paper • 2505.12532 • Published •
1
VeRA: Vector-based Random Matrix Adaptation
Paper • 2310.11454 • Published • 30 •
2
VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks
Paper • 2405.15179 • Published • 1 •
3
Uni-LoRA: One Vector is All You Need
Paper • 2506.00799 • Published • 2 •
1
Learning to Reason in 13 Parameters
Paper • 2602.04118 • Published • 6 •
1
Sparse High Rank Adapters
Paper • 2406.13175 • Published •
1
3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
Paper • 2409.00119 • Published • 1 •
1
RandLoRA: Full-rank parameter-efficient fine-tuning of large models
Paper • 2502.00987 • Published • 9 •
4