Cover Image

Sparse Matrix in Large Language Model Fine-tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Haoze, Li, Juncheng Billy, Jiang, Xuan, Miller, Heather
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning
by: He, Haoze, et al.
Published: (2026)

Sparse is Enough in Fine-tuning Pre-trained Large Language Models
by: Song, Weixi, et al.
Published: (2023)

You Only Fine-tune Once: Many-Shot In-Context Fine-Tuning for Large Language Models
by: He, Wenchong, et al.
Published: (2025)

Fine-tuning Large Language Models with Sequential Instructions
by: Hu, Hanxu, et al.
Published: (2024)

Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning
by: Tan, Zhaoxuan, et al.
Published: (2024)

Enhancing Complex Instruction Following for Large Language Models with Mixture-of-Contexts Fine-tuning
by: Lu, Yuheng, et al.
Published: (2025)

Semi-supervised Fine-tuning for Large Language Models
by: Luo, Junyu, et al.
Published: (2024)

PeFoMed: Parameter Efficient Fine-tuning of Multimodal Large Language Models for Medical Imaging
by: He, Jinlong, et al.
Published: (2024)

Detecting Bias in Large Language Models: Fine-tuned KcBERT
by: Lee, J. K., et al.
Published: (2024)

Full Parameter Fine-tuning for Large Language Models with Limited Resources
by: Lv, Kai, et al.
Published: (2023)

Non-instructional Fine-tuning: Enabling Instruction-Following Capabilities in Pre-trained Language Models without Instruction-Following Data
by: Xie, Juncheng, et al.
Published: (2024)

An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning
by: Luo, Yun, et al.
Published: (2023)

Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning Perturbation
by: Wang, Yibo, et al.
Published: (2025)

Step-by-Step Unmasking for Parameter-Efficient Fine-tuning of Large Language Models
by: Agarwal, Aradhye, et al.
Published: (2024)

Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering
by: Hu, Yinghao, et al.
Published: (2025)

A Fine-tuning Dataset and Benchmark for Large Language Models for Protein Understanding
by: Shen, Yiqing, et al.
Published: (2024)

Objective Metrics for Evaluating Large Language Models Using External Data Sources
by: Du, Haoze, et al.
Published: (2025)

Exploring Memorization in Fine-tuned Language Models
by: Zeng, Shenglai, et al.
Published: (2023)

Demystifying Instruction Mixing for Fine-tuning Large Language Models
by: Wang, Renxi, et al.
Published: (2023)

EnchTable: Unified Safety Alignment Transfer in Fine-tuned Large Language Models
by: Wu, Jialin, et al.
Published: (2025)

KnowTuning: Knowledge-aware Fine-tuning for Large Language Models
by: Lyu, Yougang, et al.
Published: (2024)

Fine-tuning Large Language Models for Domain-specific Machine Translation
by: Zheng, Jiawei, et al.
Published: (2024)

JudgeLM: Fine-tuned Large Language Models are Scalable Judges
by: Zhu, Lianghui, et al.
Published: (2023)

Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation
by: Bellaouar, Slimane, et al.
Published: (2025)

Compositional Subspace Representation Fine-tuning for Adaptive Large Language Models
by: Zhou, Andy
Published: (2025)

A Study of Backdoors in Instruction Fine-tuned Language Models
by: Raghuram, Jayaram, et al.
Published: (2024)

Large Language Model for Multi-Domain Translation: Benchmarking and Domain CoT Fine-tuning
by: Hu, Tianxiang, et al.
Published: (2024)

ALoRA: Allocating Low-Rank Adaptation for Fine-tuning Large Language Models
by: Liu, Zequan, et al.
Published: (2024)

Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification
by: Meng, Tao, et al.
Published: (2024)

Assertion Detection Large Language Model In-context Learning LoRA Fine-tuning
by: Ji, Yuelyu, et al.
Published: (2024)

Let's Focus on Neuron: Neuron-Level Supervised Fine-tuning for Large Language Model
by: Xu, Haoyun, et al.
Published: (2024)

Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
by: Bai, Jiamu, et al.
Published: (2024)

Data-efficient LLM Fine-tuning for Code Generation
by: Lv, Weijie, et al.
Published: (2025)

Plug-in and Fine-tuning: Bridging the Gap between Small Language Models and Large Language Models
by: Kim, Kyeonghyun, et al.
Published: (2025)

Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
by: Yin, Haoteng, et al.
Published: (2024)

Prompting or Fine-tuning? Exploring Large Language Models for Causal Graph Validation
by: Susanti, Yuni, et al.
Published: (2024)

MoA: Heterogeneous Mixture of Adapters for Parameter-Efficient Fine-Tuning of Large Language Models
by: Cao, Jie, et al.
Published: (2025)

RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning
by: Wang, Haoyu, et al.
Published: (2024)

Efficient Model Editing with Task-Localized Sparse Fine-tuning
by: Iurada, Leonardo, et al.
Published: (2025)

InsCL: A Data-efficient Continual Learning Paradigm for Fine-tuning Large Language Models with Instructions
by: Wang, Yifan, et al.
Published: (2024)