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Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Paper • 2403.14608 • Published -
Towards Better Parameter-Efficient Fine-Tuning for Large Language Models: A Position Paper
Paper • 2311.13126 • Published • 1 -
Comparing Retrieval-Augmentation and Parameter-Efficient Fine-Tuning for Privacy-Preserving Personalization of Large Language Models
Paper • 2409.09510 • Published -
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
Paper • 2407.01320 • Published
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Collections including paper arxiv:2403.14608
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Instruction Tuning for Large Language Models: A Survey
Paper • 2308.10792 • Published • 1 -
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Paper • 2403.14608 • Published -
Efficient Large Language Models: A Survey
Paper • 2312.03863 • Published • 4 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 32
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A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings
Paper • 2504.15610 • Published • 1 -
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Paper • 2502.13533 • Published • 13 -
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
Paper • 2403.08822 • Published -
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
Paper • 2407.18242 • Published
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Instruction Mining: High-Quality Instruction Data Selection for Large Language Models
Paper • 2307.06290 • Published • 10 -
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models
Paper • 2408.02085 • Published • 19 -
A Survey on Data Selection for LLM Instruction Tuning
Paper • 2402.05123 • Published • 3 -
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Paper • 2403.14608 • Published
-
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Paper • 2403.14608 • Published -
Towards Better Parameter-Efficient Fine-Tuning for Large Language Models: A Position Paper
Paper • 2311.13126 • Published • 1 -
Comparing Retrieval-Augmentation and Parameter-Efficient Fine-Tuning for Privacy-Preserving Personalization of Large Language Models
Paper • 2409.09510 • Published -
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
Paper • 2407.01320 • Published
-
A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings
Paper • 2504.15610 • Published • 1 -
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Paper • 2502.13533 • Published • 13 -
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
Paper • 2403.08822 • Published -
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
Paper • 2407.18242 • Published
-
Instruction Mining: High-Quality Instruction Data Selection for Large Language Models
Paper • 2307.06290 • Published • 10 -
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models
Paper • 2408.02085 • Published • 19 -
A Survey on Data Selection for LLM Instruction Tuning
Paper • 2402.05123 • Published • 3 -
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Paper • 2403.14608 • Published
-
Instruction Tuning for Large Language Models: A Survey
Paper • 2308.10792 • Published • 1 -
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Paper • 2403.14608 • Published -
Efficient Large Language Models: A Survey
Paper • 2312.03863 • Published • 4 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 32