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Collections including paper arxiv:2310.00035

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22, 2025 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19, 2025 • 13
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

Papers: MoE/Ensemble

Papers related to Mixture of Experts topics.

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 27
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
The Consensus Game: Language Model Generation via Equilibrium Search

Paper • 2310.09139 • Published Oct 13, 2023 • 14
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning

Paper • 2310.03094 • Published Oct 4, 2023 • 13

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 27
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
Diversity of Thought Improves Reasoning Abilities of Large Language Models

Paper • 2310.07088 • Published Oct 11, 2023 • 5
AutoMix: Automatically Mixing Language Models

Paper • 2310.12963 • Published Oct 19, 2023 • 14
SAI: Solving AI Tasks with Systematic Artificial Intelligence in Communication Network

Paper • 2310.09049 • Published Oct 13, 2023 • 1

Papers related to parameter efficient finetuning methods.

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45

LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
LoRA Learns Less and Forgets Less

Paper • 2405.09673 • Published May 15, 2024 • 91

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22, 2025 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19, 2025 • 13
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

Papers related to parameter efficient finetuning methods.

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45

Papers: MoE/Ensemble

Papers related to Mixture of Experts topics.

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 27
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
The Consensus Game: Language Model Generation via Equilibrium Search

Paper • 2310.09139 • Published Oct 13, 2023 • 14
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning

Paper • 2310.03094 • Published Oct 4, 2023 • 13

LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
LoRA Learns Less and Forgets Less

Paper • 2405.09673 • Published May 15, 2024 • 91

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 27
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
Diversity of Thought Improves Reasoning Abilities of Large Language Models

Paper • 2310.07088 • Published Oct 11, 2023 • 5
AutoMix: Automatically Mixing Language Models

Paper • 2310.12963 • Published Oct 19, 2023 • 14
SAI: Solving AI Tasks with Systematic Artificial Intelligence in Communication Network

Paper • 2310.09049 • Published Oct 13, 2023 • 1

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