Copertina

Phased Instruction Fine-Tuning for Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pang, Wei, Zhou, Chuan, Zhou, Xiao-Hua, Wang, Xiaojie
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning
di: Zhang, Zhongjian, et al.
Pubblicazione: (2026)

Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning
di: Zhang, Xinlu, et al.
Pubblicazione: (2024)

Towards Robust Instruction Tuning on Multimodal Large Language Models
di: Han, Wei, et al.
Pubblicazione: (2024)

GraphGPT: Graph Instruction Tuning for Large Language Models
di: Tang, Jiabin, et al.
Pubblicazione: (2023)

Investigating Instruction Tuning Large Language Models on Graphs
di: Zhu, Kerui, et al.
Pubblicazione: (2024)

Optimizing Psychological Counseling with Instruction-Tuned Large Language Models
di: Li, Wenjie, et al.
Pubblicazione: (2024)

Memorization in Fine-Tuned Large Language Models
di: Savine, Danil
Pubblicazione: (2025)

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning
di: Peng, Cheng, et al.
Pubblicazione: (2025)

SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe
di: Xiao, Yuxin, et al.
Pubblicazione: (2024)

Instructional Fingerprinting of Large Language Models
di: Xu, Jiashu, et al.
Pubblicazione: (2024)

Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models
di: Xu, Jiashu, et al.
Pubblicazione: (2023)

Safety-Aware Fine-Tuning of Large Language Models
di: Choi, Hyeong Kyu, et al.
Pubblicazione: (2024)

STAR: Constraint LoRA with Dynamic Active Learning for Data-Efficient Fine-Tuning of Large Language Models
di: Zhang, Linhai, et al.
Pubblicazione: (2024)

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

Instruction Mining: Instruction Data Selection for Tuning Large Language Models
di: Cao, Yihan, et al.
Pubblicazione: (2023)

OctoPack: Instruction Tuning Code Large Language Models
di: Muennighoff, Niklas, et al.
Pubblicazione: (2023)

Penrose Tiled Low-Rank Compression and Section-Wise Q&A Fine-Tuning: A General Framework for Domain-Specific Large Language Model Adaptation
di: Kuo, Chuan-Wei, et al.
Pubblicazione: (2025)

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

Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models
di: Barnett, Scott, et al.
Pubblicazione: (2024)

Graph-oriented Instruction Tuning of Large Language Models for Generic Graph Mining
di: Tan, Yanchao, et al.
Pubblicazione: (2024)

Instruction Tuning for Large Language Models: A Survey
di: Zhang, Shengyu, et al.
Pubblicazione: (2023)

Improved Supervised Fine-Tuning for Large Language Models to Mitigate Catastrophic Forgetting
di: Ding, Fei, et al.
Pubblicazione: (2025)

RoSA: Enhancing Parameter-Efficient Fine-Tuning via RoPE-aware Selective Adaptation in Large Language Models
di: Pan, Dayan, et al.
Pubblicazione: (2025)

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

Reversing Large Language Models for Efficient Training and Fine-Tuning
di: Gal, Eshed, et al.
Pubblicazione: (2025)

Impact of Fine-Tuning Methods on Memorization in Large Language Models
di: Hou, Jie, et al.
Pubblicazione: (2025)

Boosting Large Language Models with Mask Fine-Tuning
di: Zhang, Mingyuan, et al.
Pubblicazione: (2025)

LIFEBench: Evaluating Length Instruction Following in Large Language Models
di: Zhang, Wei, et al.
Pubblicazione: (2025)

DELIA: Diversity-Enhanced Learning for Instruction Adaptation in Large Language Models
di: Zeng, Yuanhao, et al.
Pubblicazione: (2024)

LARFT: Closing the Cognition-Action Gap for Length Instruction Following in Large Language Models
di: Zhang, Wei, et al.
Pubblicazione: (2026)

TCM-FTP: Fine-Tuning Large Language Models for Herbal Prescription Prediction
di: Zhou, Xingzhi, et al.
Pubblicazione: (2024)

InstructAV: Instruction Fine-tuning Large Language Models for Authorship Verification
di: Hu, Yujia, et al.
Pubblicazione: (2024)

BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing
di: Tran, Hieu, et al.
Pubblicazione: (2023)

Parameter-Efficient Fine-Tuning With Adapters
di: Chen, Keyu, et al.
Pubblicazione: (2024)

Crafting Efficient Fine-Tuning Strategies for Large Language Models
di: Oliver, Michael, et al.
Pubblicazione: (2024)

Rethinking Supervised Fine-Tuning: Emphasizing Key Answer Tokens for Improved LLM Accuracy
di: Shi, Xiaofeng, et al.
Pubblicazione: (2025)

Efficient Fine-Tuning of Large Language Models for Automated Medical Documentation
di: Leong, Hui Yi, et al.
Pubblicazione: (2024)

Noise Augmented Fine Tuning for Mitigating Hallucinations in Large Language Models
di: Khadangi, Afshin, et al.
Pubblicazione: (2025)

CrisisSense-LLM: Instruction Fine-Tuned Large Language Model for Multi-label Social Media Text Classification in Disaster Informatics
di: Yin, Kai, et al.
Pubblicazione: (2024)

Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models for Russian
di: Nikolich, Aleksandr, et al.
Pubblicazione: (2024)