:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Lei, Ye, Zikun, Zhao, Jinglong
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2511.19486
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning
by: Ye, Kai, et al.
Published: (2025)

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

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
by: Wei, Quan, et al.
Published: (2025)

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models
by: Zhang, Longteng, et al.
Published: (2026)

Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models
by: Fang, Zihan, et al.
Published: (2024)

Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
by: Chow, Yinlam, et al.
Published: (2024)

GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification
by: Gan, Wangjie, et al.
Published: (2026)

On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
by: Wang, Shumin, et al.
Published: (2026)

A Bayesian Hybrid Parameter-Efficient Fine-Tuning Method for Large Language Models
by: Chai, Yidong, et al.
Published: (2025)

The Effectiveness of Approximate Regularized Replay for Efficient Supervised Fine-Tuning of Large Language Models
by: Riemer, Matthew, et al.
Published: (2025)

FedKRSO: Communication and Memory Efficient Federated Fine-Tuning of Large Language Models
by: Yang, Guohao, et al.
Published: (2026)

Understanding and Guiding Layer Placement in Parameter-Efficient Fine-Tuning of Large Language Models
by: Xu, Yichen, et al.
Published: (2026)

TuneComp: Joint Fine-tuning and Compression for Large Foundation Models
by: Chen, Xiangyu, et al.
Published: (2025)

Linearization Explains Fine-Tuning in Large Language Models
by: Afzal, Zahra Rahimi, et al.
Published: (2026)

MELINOE: Fine-Tuning Enables Memory-Efficient Inference for Mixture-of-Experts Models
by: Raje, Arian, et al.
Published: (2026)

FZOO: Fast Zeroth-Order Optimizer for Fine-Tuning Large Language Models towards Adam-Scale Speed
by: Dang, Sizhe, et al.
Published: (2025)

Exploring Gradient Subspaces: Addressing and Overcoming LoRA's Limitations in Federated Fine-Tuning of Large Language Models
by: Mahla, Navyansh, et al.
Published: (2024)

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

Adaptive Defense against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler
by: Hu, Zixuan, et al.
Published: (2025)

A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning
by: Bian, Jieming, et al.
Published: (2025)

Efficient Federated Fine-Tuning of Large Language Models with Layer Dropout
by: Wang, Shilong, et al.
Published: (2025)

PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
by: Liu, Yi, et al.
Published: (2025)

QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models
by: Zhou, Jiajun, et al.
Published: (2025)

IRIS: Interpolative Rényi Iterative Self-play for Large Language Model Fine-Tuning
by: Liao, Wenjie, et al.
Published: (2026)

Preserving Diversity in Supervised Fine-Tuning of Large Language Models
by: Li, Ziniu, et al.
Published: (2024)

Multi-Level Safety Continual Projection for Fine-Tuned Large Language Models without Retraining
by: Han, Bing, et al.
Published: (2025)

BEFT: Bias-Efficient Fine-Tuning of Language Models in Low-Data Regimes
by: Huang, Baichuan, et al.
Published: (2025)

Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning
by: Pasewark, Eric, et al.
Published: (2024)

LLM in a flash: Efficient Large Language Model Inference with Limited Memory
by: Alizadeh, Keivan, et al.
Published: (2023)

Efficient Low Rank Attention for Long-Context Inference in Large Language Models
by: Li, Tenghui, et al.
Published: (2025)

Efficient and Scalable Fine-Tune of Language Models for Genome Understanding
by: Zhan, Huixin, et al.
Published: (2024)

BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models
by: Chang, Aofei, et al.
Published: (2024)

Federated Data-Efficient Instruction Tuning for Large Language Models
by: Qin, Zhen, et al.
Published: (2024)

Scaling Sparse Fine-Tuning to Large Language Models
by: Ansell, Alan, et al.
Published: (2024)

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

TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2025)

PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models
by: Agiza, Ahmed, et al.
Published: (2024)

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

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models
by: Kim, Gyuhak, et al.
Published: (2025)

Reinforcement Learning Fine-Tunes a Sparse Subnetwork in Large Language Models
by: Balashov, Andrii
Published: (2025)