Image de couverture de livre

FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Gao, Yan, Scamarcia, Massimo Roberto, Fernandez-Marques, Javier, Naseri, Mohammad, Ng, Chong Shen, Stripelis, Dimitris, Li, Zexi, Shen, Tao, Bai, Jiamu, Chen, Daoyuan, Zhang, Zikai, Hu, Rui, Song, InSeo, KangYoon, Lee, Jia, Hong, Dang, Ting, Wang, Junyan, Liu, Zheyuan, Beutel, Daniel Janes, Lyu, Lingjuan, Lane, Nicholas D.
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Supercharging Federated Intelligence Retrieval
par: Stripelis, Dimitris, et autres
Publié: (2026)

On the Convergence of Zeroth-Order Federated Tuning for Large Language Models
par: Ling, Zhenqing, et autres
Publié: (2024)

Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data
par: Ling, Zhenqing, et autres
Publié: (2025)

MindGYM: What Matters in Question Synthesis for Thinking-Centric Fine-Tuning?
par: Xu, Zhe, et autres
Publié: (2025)

EdgeFlowerTune: Evaluating Federated LLM Fine-Tuning Under Realistic Edge System Constraints
par: Geng, Jiaxiang, et autres
Publié: (2026)

Frame-wise Conditioning Adaptation for Fine-Tuning Diffusion Models in Text-to-Video Prediction
par: Liu, Zheyuan, et autres
Publié: (2025)

FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
par: Wang, Ziyao, et autres
Publié: (2024)

Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation
par: Zhang, Zikai, et autres
Publié: (2026)

Differentiation-Based Extraction of Proprietary Data from Fine-Tuned LLMs
par: Li, Zongjie, et autres
Publié: (2025)

Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
par: Bai, Jiamu, et autres
Publié: (2024)

SEAT: Sparse Entity-Aware Tuning for Knowledge Adaptation while Preserving Epistemic Abstention
par: Shen, William F., et autres
Publié: (2025)

Rethinking Data Selection for Supervised Fine-Tuning
par: Shen, Ming
Publié: (2024)

Diversity Measurement and Subset Selection for Instruction Tuning Datasets
par: Wang, Peiqi, et autres
Publié: (2024)

The Convergence of Dynamic Routing between Capsules
par: Ye, Daoyuan, et autres
Publié: (2025)

Can LLMs Generate High-Quality Test Cases for Algorithm Problems? TestCase-Eval: A Systematic Evaluation of Fault Coverage and Exposure
par: Yang, Zheyuan, et autres
Publié: (2025)

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits
par: Zhou, Zikai, et autres
Publié: (2025)

Fed-pilot: Optimizing LoRA Allocation for Efficient Federated Fine-Tuning with Heterogeneous Clients
par: Zhang, Zikai, et autres
Publié: (2024)

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation
par: Zhang, Zikai, et autres
Publié: (2025)

Supercharging Federated Learning with Flower and NVIDIA FLARE
par: Roth, Holger R., et autres
Publié: (2024)

Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
par: Qin, Zhen, et autres
Publié: (2023)

Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning
par: Zhao, Shuai, et autres
Publié: (2024)

Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs
par: Hu, Zixuan, et autres
Publié: (2024)

Budgeted Online Model Selection and Fine-Tuning via Federated Learning
par: Ghari, Pouya M., et autres
Publié: (2024)

A Flower-Inspired Solution for Computer Memory Wear-Leveling
par: Shen, Elizabeth, et autres
Publié: (2025)

Zero-Shot Code Representation Learning via Prompt Tuning
par: Cui, Nan, et autres
Publié: (2024)

MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
par: Han, Jing, et autres
Publié: (2025)

DePT: Decoupled Prompt Tuning
par: Zhang, Ji, et autres
Publié: (2023)

Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications
par: Ma, Wei, et autres
Publié: (2024)

Med-Tuning: A New Parameter-Efficient Tuning Framework for Medical Volumetric Segmentation
par: Shen, Jiachen, et autres
Publié: (2023)

GiFT: Gibbs Fine-Tuning for Code Generation
par: Li, Haochen, et autres
Publié: (2025)

Call for Rigor in Reporting Quality of Instruction Tuning Data
par: Moon, Hyeonseok, et autres
Publié: (2025)

Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning
par: Ghari, Pouya M., et autres
Publié: (2024)

Instruction Tuning for Story Understanding and Generation with Weak Supervision
par: Yuan, Yangshu, et autres
Publié: (2025)

Expanding Sparse Tuning for Low Memory Usage
par: Shen, Shufan, et autres
Publié: (2024)

Iterative Method for Tuning Complex Simulation Code
par: Seo, Yun Am, et autres
Publié: (2020)

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates
par: Ma, Chenyang, et autres
Publié: (2023)

mEdIT: Multilingual Text Editing via Instruction Tuning
par: Raheja, Vipul, et autres
Publié: (2024)

Instruction Tuning with and without Context: Behavioral Shifts and Downstream Impact
par: Lee, Hyunji, et autres
Publié: (2025)

Enhancing Faithfulness in Abstractive Summarization via Span-Level Fine-Tuning
par: Huang, Sicong, et autres
Publié: (2025)

AutoEdit: Automatic Hyperparameter Tuning for Image Editing
par: Pham, Chau, et autres
Publié: (2025)