PockEngine: Sparse and Efficient Fine-tuning in a Pocket
Paper
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2310.17752
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Published
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12
Fine-Tuning
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S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Paper • 2311.03285 • Published • 28 -
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Paper • 2311.06243 • Published • 17 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 28 -
SiRA: Sparse Mixture of Low Rank Adaptation
Paper • 2311.09179 • Published • 8 -
Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning
Paper • 2311.11077 • Published • 24 -
LLaMA Pro: Progressive LLaMA with Block Expansion
Paper • 2401.02415 • Published • 53 -
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 19 -
How to Train Data-Efficient LLMs
Paper • 2402.09668 • Published • 40 -
A Survey on Data Selection for LLM Instruction Tuning
Paper • 2402.05123 • Published • 3 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 46 -
Towards Modular LLMs by Building and Reusing a Library of LoRAs
Paper • 2405.11157 • Published • 27 -
Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning
Paper • 2405.17258 • Published • 14 -
In-Context Editing: Learning Knowledge from Self-Induced Distributions
Paper • 2406.11194 • Published • 15 -
Iterative Length-Regularized Direct Preference Optimization: A Case Study on Improving 7B Language Models to GPT-4 Level
Paper • 2406.11817 • Published • 12 -
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
Paper • 2409.06277 • Published • 14