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Collections including paper arxiv:2402.05123

I add and I forget to read

Adapt-Pruner: Adaptive Structural Pruning for Efficient Small Language Model Training

Paper • 2502.03460 • Published Feb 5
LLM-Pruner: On the Structural Pruning of Large Language Models

Paper • 2305.11627 • Published May 19, 2023 • 3
Pruning as a Domain-specific LLM Extractor

Paper • 2405.06275 • Published May 10, 2024 • 1
KnowTuning: Knowledge-aware Fine-tuning for Large Language Models

Paper • 2402.11176 • Published Feb 17, 2024 • 2

A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development

Paper • 2407.11784 • Published Jul 16, 2024 • 4
Data Management For Large Language Models: A Survey

Paper • 2312.01700 • Published Dec 4, 2023
Datasets for Large Language Models: A Comprehensive Survey

Paper • 2402.18041 • Published Feb 28, 2024 • 2

Instruction Tuning

A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
WaveCoder: Widespread And Versatile Enhanced Instruction Tuning with Refined Data Generation

Paper • 2312.14187 • Published Dec 20, 2023 • 50
Generative Representational Instruction Tuning

Paper • 2402.09906 • Published Feb 15, 2024 • 54
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20, 2024 • 26

PockEngine: Sparse and Efficient Fine-tuning in a Pocket

Paper • 2310.17752 • Published Oct 26, 2023 • 15
S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Paper • 2311.03285 • Published Nov 6, 2023 • 32
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization

Paper • 2311.06243 • Published Nov 10, 2023 • 22
Fine-tuning Language Models for Factuality

Paper • 2311.08401 • Published Nov 14, 2023 • 30

Instruction Tuning

Instruction Mining: High-Quality Instruction Data Selection for Large Language Models

Paper • 2307.06290 • Published Jul 12, 2023 • 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 Aug 4, 2024 • 19
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Paper • 2403.14608 • Published Mar 21, 2024

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation

Paper • 2409.12941 • Published Sep 19, 2024 • 24
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62

Data-efficient LLMs

dataset pruning for advancing the capabilities of LLMs

Effective pruning of web-scale datasets based on complexity of concept clusters

Paper • 2401.04578 • Published Jan 9, 2024
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
LESS: Selecting Influential Data for Targeted Instruction Tuning

Paper • 2402.04333 • Published Feb 6, 2024 • 3

I add and I forget to read

Adapt-Pruner: Adaptive Structural Pruning for Efficient Small Language Model Training

Paper • 2502.03460 • Published Feb 5
LLM-Pruner: On the Structural Pruning of Large Language Models

Paper • 2305.11627 • Published May 19, 2023 • 3
Pruning as a Domain-specific LLM Extractor

Paper • 2405.06275 • Published May 10, 2024 • 1
KnowTuning: Knowledge-aware Fine-tuning for Large Language Models

Paper • 2402.11176 • Published Feb 17, 2024 • 2

Instruction Tuning

Instruction Mining: High-Quality Instruction Data Selection for Large Language Models

Paper • 2307.06290 • Published Jul 12, 2023 • 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 Aug 4, 2024 • 19
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Paper • 2403.14608 • Published Mar 21, 2024

A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development

Paper • 2407.11784 • Published Jul 16, 2024 • 4
Data Management For Large Language Models: A Survey

Paper • 2312.01700 • Published Dec 4, 2023
Datasets for Large Language Models: A Comprehensive Survey

Paper • 2402.18041 • Published Feb 28, 2024 • 2

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation

Paper • 2409.12941 • Published Sep 19, 2024 • 24
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62

Instruction Tuning

A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
WaveCoder: Widespread And Versatile Enhanced Instruction Tuning with Refined Data Generation

Paper • 2312.14187 • Published Dec 20, 2023 • 50
Generative Representational Instruction Tuning

Paper • 2402.09906 • Published Feb 15, 2024 • 54
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20, 2024 • 26

Data-efficient LLMs

dataset pruning for advancing the capabilities of LLMs

Effective pruning of web-scale datasets based on complexity of concept clusters

Paper • 2401.04578 • Published Jan 9, 2024
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4, 2024 • 3
LESS: Selecting Influential Data for Targeted Instruction Tuning

Paper • 2402.04333 • Published Feb 6, 2024 • 3

PockEngine: Sparse and Efficient Fine-tuning in a Pocket

Paper • 2310.17752 • Published Oct 26, 2023 • 15
S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Paper • 2311.03285 • Published Nov 6, 2023 • 32
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization

Paper • 2311.06243 • Published Nov 10, 2023 • 22
Fine-tuning Language Models for Factuality

Paper • 2311.08401 • Published Nov 14, 2023 • 30

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