Copertina

Instruction Tuning for Large Language Models: A Survey

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Shengyu, Dong, Linfeng, Li, Xiaoya, Zhang, Sen, Sun, Xiaofei, Wang, Shuhe, Li, Jiwei, Hu, Runyi, Zhang, Tianwei, Wu, Fei, Wang, Guoyin
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Reinforcement Learning Enhanced LLMs: A Survey
di: Wang, Shuhe, et al.
Pubblicazione: (2024)

Turn That Frown Upside Down: FaceID Customization via Cross-Training Data
di: Wang, Shuhe, et al.
Pubblicazione: (2025)

Picky LLMs and Unreliable RMs: An Empirical Study on Safety Alignment after Instruction Tuning
di: Li, Guanlin, et al.
Pubblicazione: (2025)

Packing Analysis: Packing Is More Appropriate for Large Models or Datasets in Supervised Fine-tuning
di: Wang, Shuhe, et al.
Pubblicazione: (2024)

FaceID-6M: A Large-Scale, Open-Source FaceID Customization Dataset
di: Wang, Shuhe, et al.
Pubblicazione: (2025)

Robust-Wide: Robust Watermarking against Instruction-driven Image Editing
di: Hu, Runyi, et al.
Pubblicazione: (2024)

CRINN: Contrastive Reinforcement Learning for Approximate Nearest Neighbor Search
di: Li, Xiaoya, et al.
Pubblicazione: (2025)

Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation
di: Lv, Zheqi, et al.
Pubblicazione: (2025)

Retrieval Augmented Instruction Tuning for Open NER with Large Language Models
di: Xie, Tingyu, et al.
Pubblicazione: (2024)

Template-assisted Contrastive Learning of Task-oriented Dialogue Sentence Embeddings
di: Oh, Minsik, et al.
Pubblicazione: (2023)

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

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

Dynamics of Instruction Fine-Tuning for Chinese Large Language Models
di: Song, Chiyu, et al.
Pubblicazione: (2023)

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

Inference-time Alignment via Sparse Junction Steering
di: Hu, Runyi, et al.
Pubblicazione: (2026)

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

Towards Building the Federated GPT: Federated Instruction Tuning
di: Zhang, Jianyi, et al.
Pubblicazione: (2023)

EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language Models
di: Zou, Tao, et al.
Pubblicazione: (2025)

PK-ICR: Persona-Knowledge Interactive Context Retrieval for Grounded Dialogue
di: Oh, Minsik, et al.
Pubblicazione: (2023)

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

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

A Survey on Data Selection for LLM Instruction Tuning
di: Zhang, Bolin, et al.
Pubblicazione: (2024)

Learning Instruction-Following Policies through Open-Ended Instruction Relabeling with Large Language Models
di: Zhang, Zhicheng, et al.
Pubblicazione: (2025)

Similarity-based Neighbor Selection for Graph LLMs
di: Li, Rui, et al.
Pubblicazione: (2024)

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)

HFT: Half Fine-Tuning for Large Language Models
di: Hui, Tingfeng, et al.
Pubblicazione: (2024)

Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
di: Li, Haoran, et al.
Pubblicazione: (2024)

Efficient Attention Mechanisms for Large Language Models: A Survey
di: Sun, Yutao, et al.
Pubblicazione: (2025)

Efficient Tuning of Large Language Models for Knowledge-Grounded Dialogue Generation
di: Zhang, Bo, et al.
Pubblicazione: (2025)

Large Language Model Instruction Following: A Survey of Progresses and Challenges
di: Lou, Renze, et al.
Pubblicazione: (2023)

HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model
di: Guo, Haiyang, et al.
Pubblicazione: (2025)

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies
di: Xiong, Tao, et al.
Pubblicazione: (2025)

Upcycling Instruction Tuning from Dense to Mixture-of-Experts via Parameter Merging
di: Hui, Tingfeng, et al.
Pubblicazione: (2024)

VideoShield: Regulating Diffusion-based Video Generation Models via Watermarking
di: Hu, Runyi, et al.
Pubblicazione: (2025)

A Survey on Large Language Model Benchmarks
di: Ni, Shiwen, et al.
Pubblicazione: (2025)

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

DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning
di: Wang, Yejie, et al.
Pubblicazione: (2024)

INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning
di: Zhu, Yutao, et al.
Pubblicazione: (2024)

LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning
di: You, Zebin, et al.
Pubblicazione: (2025)

Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
di: Wang, Luping, et al.
Pubblicazione: (2024)