Cover Image

Efficient End-to-end Language Model Fine-tuning on Graphs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xue, Rui, Shen, Xipeng, Yu, Ruozhou, Liu, Xiaorui
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models
by: Chen, Pin-Yu, et al.
Published: (2025)

Efficient Model Development through Fine-tuning Transfer
by: Lin, Pin-Jie, et al.
Published: (2025)

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

LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
by: Chen, Yukang, et al.
Published: (2023)

Fine-tuning Language Models with Generative Adversarial Reward Modelling
by: Yu, Zhang Ze, et al.
Published: (2023)

How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition
by: Dong, Guanting, et al.
Published: (2023)

Information Guided Regularization for Fine-tuning Language Models
by: Sharma, Mandar, et al.
Published: (2024)

FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition
by: Yan, Yuxuan, et al.
Published: (2024)

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

APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation
by: Marín, Javier
Published: (2025)

LaFFi: Leveraging Hybrid Natural Language Feedback for Fine-tuning Language Models
by: Li, Qianxi, et al.
Published: (2023)

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

SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection
by: Shen, Han, et al.
Published: (2024)

Selecting Large Language Model to Fine-tune via Rectified Scaling Law
by: Lin, Haowei, et al.
Published: (2024)

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

Parameter Efficient Fine-tuning via Explained Variance Adaptation
by: Paischer, Fabian, et al.
Published: (2024)

Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
by: Song, Haobo, et al.
Published: (2024)

Fine-tuning Multi-hop Question Answering with Hierarchical Graph Network
by: Xiong, Guanming
Published: (2020)

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression
by: Huang, Wei, et al.
Published: (2025)

Fine-tuning can Help Detect Pretraining Data from Large Language Models
by: Zhang, Hengxiang, et al.
Published: (2024)

Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
by: Szep, Marton, et al.
Published: (2024)

Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
by: Xu, Jing, et al.
Published: (2024)

Harnessing Large Language Models: Fine-tuned BERT for Detecting Charismatic Leadership Tactics in Natural Language
by: Saeid, Yasser, et al.
Published: (2024)

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
by: Zhang, Renrui, et al.
Published: (2023)

SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
by: Yang, Yu, et al.
Published: (2024)

Outlier-weighed Layerwise Sampling for LLM Fine-tuning
by: Li, Pengxiang, et al.
Published: (2024)

Parameter-Efficient Fine-Tuning for Foundation Models
by: Zhang, Dan, et al.
Published: (2025)

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

Mechanistic Fine-tuning for In-context Learning
by: Cho, Hakaze, et al.
Published: (2025)

Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models
by: Peng, Zhiyuan, et al.
Published: (2024)

AMAQ: Adaptive Mixed-bit Activation Quantization for Collaborative Parameter Efficient Fine-tuning
by: Song, Yurun, et al.
Published: (2025)

PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning
by: Zou, Jiaru, et al.
Published: (2024)

LLM4DistReconfig: A Fine-tuned Large Language Model for Power Distribution Network Reconfiguration
by: Christou, Panayiotis, et al.
Published: (2025)

G-Loss: Graph-Guided Fine-Tuning of Language Models
by: Sharma, Aditya, et al.
Published: (2026)

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

Virus: Harmful Fine-tuning Attack for Large Language Models Bypassing Guardrail Moderation
by: Huang, Tiansheng, et al.
Published: (2025)

Explain Less, Understand More: Jargon Detection via Personalized Parameter-Efficient Fine-tuning
by: Wu, Bohao, et al.
Published: (2025)

The Impact of Fine-tuning Large Language Models on Automated Program Repair
by: Macháček, Roman, et al.
Published: (2025)

Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning
by: Lee, Yu-Ang, et al.
Published: (2026)

Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance
by: Ye, Jiasheng, et al.
Published: (2024)