Cover Image

FedQuad: Adaptive Layer-wise LoRA Deployment and Activation Quantization for Federated Fine-Tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Rukuo, Liu, Jianchun, Xu, Hongli, Huang, Liusheng
Format:	Preprint
Published:	2025
Subjects:	Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning
by: Huo, Yujia, et al.
Published: (2025)

Fed-pilot: Optimizing LoRA Allocation for Efficient Federated Fine-Tuning with Heterogeneous Clients
by: Zhang, Zikai, et al.
Published: (2024)

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation
by: Zhang, Zikai, et al.
Published: (2025)

pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023)

Towards Communication-Efficient Decentralized Federated Graph Learning over Non-IID Data
by: Wang, Shilong, et al.
Published: (2025)

Many Hands Make Light Work: Accelerating Edge Inference via Multi-Client Collaborative Caching
by: Liang, Wenyi, et al.
Published: (2024)

SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA
by: Liu, Jianmin, et al.
Published: (2025)

HAFLQ: Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization
by: Su, Yang, et al.
Published: (2024)

FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning
by: QI, Jiaxing, et al.
Published: (2024)

Accelerating End-Cloud Collaborative Inference via Near Bubble-free Pipeline Optimization
by: Gao, Luyao, et al.
Published: (2024)

LoRA-C: Parameter-Efficient Fine-Tuning of Robust CNN for IoT Devices
by: Ding, Chuntao, et al.
Published: (2024)

Stabilizing Decentralized Federated Fine-Tuning via Topology-Aware Alternating LoRA
by: Wang, Xiaoyu, et al.
Published: (2026)

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

Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models
by: Cho, Yae Jee, et al.
Published: (2024)

ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads
by: Zuo, Jingwei, et al.
Published: (2026)

Caesar: A Low-deviation Compression Approach for Efficient Federated Learning
by: Yan, Jiaming, et al.
Published: (2024)

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
by: Jhunjhunwala, Divyansh, et al.
Published: (2025)

Adaptive Parameter-Efficient Federated Fine-Tuning on Heterogeneous Devices
by: Liu, Jun, et al.
Published: (2024)

FedEx-LoRA: Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models
by: Singhal, Raghav, et al.
Published: (2024)

EcoLoRA: Communication-Efficient Federated Fine-Tuning of Large Language Models
by: Liu, Han, et al.
Published: (2025)

Federated LoRA with Sparse Communication
by: Kuo, Kevin, et al.
Published: (2024)

LoRAFusion: Efficient LoRA Fine-Tuning for LLMs
by: Zhu, Zhanda, et al.
Published: (2025)

Air-FedGA: A Grouping Asynchronous Federated Learning Mechanism Exploiting Over-the-air Computation
by: Ma, Qianpiao, et al.
Published: (2025)

Collaborative Speculative Inference for Efficient LLM Inference Serving
by: Gao, Luyao, et al.
Published: (2025)

InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models
by: Chen, Hongyu, et al.
Published: (2026)

ParallelSFL: A Novel Split Federated Learning Framework Tackling Heterogeneity Issues
by: Liao, Yunming, et al.
Published: (2024)

FedFQ: Federated Learning with Fine-Grained Quantization
by: Li, Haowei, et al.
Published: (2024)

Bandwidth-Aware and Cost-Efficient Pipeline Parallel Scheduling in Geo-Distributed LLM Training
by: Zhang, Han, et al.
Published: (2026)

Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning
by: Singhal, Raghav, et al.
Published: (2025)

FedAPTA: Federated Multi-task Learning for Heterogeneous Devices with Adaptive Layer-wise Pruning and Task-aware Aggregation
by: Yu, Zhen, et al.
Published: (2025)

HLoRA: Efficient Federated Learning System for LLM Heterogeneous Fine-Tuning
by: Liu, Qianli, et al.
Published: (2025)

JORA: JAX Tensor-Parallel LoRA Library for Retrieval Augmented Fine-Tuning
by: Tahir, Anique, et al.
Published: (2024)

Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation
by: He, Xiaoxiao, et al.
Published: (2025)

SemiSFL: Split Federated Learning on Unlabeled and Non-IID Data
by: Xu, Yang, et al.
Published: (2023)

S-LoRA: Serving Thousands of Concurrent LoRA Adapters
by: Sheng, Ying, et al.
Published: (2023)

Cross-region Model Training with Communication-Computation Overlapping and Delay Compensation
by: Zhu, Ying, et al.
Published: (2025)

Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA
by: Chen, Shuangyi, et al.
Published: (2024)

RBLA: Rank-Based-LoRA-Aggregation for Fine-tuning Heterogeneous Models in FLaaS
by: Chen, Shuaijun, et al.
Published: (2024)

Improving LoRA in Privacy-preserving Federated Learning
by: Sun, Youbang, et al.
Published: (2024)

ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning
by: Wang, Xiaoyu, et al.
Published: (2025)