Saved in:
| Main Authors: | Wang, Xiaoyu, Li, Xiaotian, Zhou, Zhixiang, Li, Chen, Liu, Yong |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.00451 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning
by: Wang, Xiaoyu, et al.
Published: (2025)
by: Wang, Xiaoyu, et al.
Published: (2025)
pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023)
by: Yi, Liping, et al.
Published: (2023)
Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA
by: Chen, Shuangyi, et al.
Published: (2024)
by: Chen, Shuangyi, et al.
Published: (2024)
Fed-pilot: Optimizing LoRA Allocation for Efficient Federated Fine-Tuning with Heterogeneous Clients
by: Zhang, Zikai, et al.
Published: (2024)
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)
by: Zhang, Zikai, et al.
Published: (2025)
Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models
by: Cho, Yae Jee, et al.
Published: (2024)
by: Cho, Yae Jee, et al.
Published: (2024)
Federated LoRA with Sparse Communication
by: Kuo, Kevin, et al.
Published: (2024)
by: Kuo, Kevin, et al.
Published: (2024)
LoRAFusion: Efficient LoRA Fine-Tuning for LLMs
by: Zhu, Zhanda, et al.
Published: (2025)
by: Zhu, Zhanda, et al.
Published: (2025)
ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads
by: Zuo, Jingwei, et al.
Published: (2026)
by: Zuo, Jingwei, et al.
Published: (2026)
FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
by: Jhunjhunwala, Divyansh, et al.
Published: (2025)
by: Jhunjhunwala, Divyansh, et al.
Published: (2025)
Improving LoRA in Privacy-preserving Federated Learning
by: Sun, Youbang, et al.
Published: (2024)
by: Sun, Youbang, et al.
Published: (2024)
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
by: Sheng, Ying, et al.
Published: (2023)
by: Sheng, Ying, et al.
Published: (2023)
SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA
by: Liu, Jianmin, et al.
Published: (2025)
by: Liu, Jianmin, et al.
Published: (2025)
JORA: JAX Tensor-Parallel LoRA Library for Retrieval Augmented Fine-Tuning
by: Tahir, Anique, et al.
Published: (2024)
by: Tahir, Anique, et al.
Published: (2024)
ServerlessLoRA: Minimizing Latency and Cost in Serverless Inference for LoRA-Based LLMs
by: Sui, Yifan, et al.
Published: (2025)
by: Sui, Yifan, et al.
Published: (2025)
RBLA: Rank-Based-LoRA-Aggregation for Fine-tuning Heterogeneous Models in FLaaS
by: Chen, Shuaijun, et al.
Published: (2024)
by: Chen, Shuaijun, et al.
Published: (2024)
HAFLQ: Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization
by: Su, Yang, et al.
Published: (2024)
by: Su, Yang, et al.
Published: (2024)
FedQuad: Adaptive Layer-wise LoRA Deployment and Activation Quantization for Federated Fine-Tuning
by: Li, Rukuo, et al.
Published: (2025)
by: Li, Rukuo, et al.
Published: (2025)
Decentralized Federated Learning with Model Caching on Mobile Agents
by: Wang, Xiaoyu, et al.
Published: (2024)
by: Wang, Xiaoyu, et al.
Published: (2024)
Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation
by: He, Xiaoxiao, et al.
Published: (2025)
by: He, Xiaoxiao, et al.
Published: (2025)
AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning
by: Chen, Shuaijun, et al.
Published: (2024)
by: Chen, Shuaijun, et al.
Published: (2024)
Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning
by: Singhal, Raghav, et al.
Published: (2025)
by: Singhal, Raghav, et al.
Published: (2025)
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
by: Wang, Ziyao, et al.
Published: (2024)
by: Wang, Ziyao, et al.
Published: (2024)
FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning
by: QI, Jiaxing, et al.
Published: (2024)
by: QI, Jiaxing, et al.
Published: (2024)
ForkKV: Scaling Multi-LoRA Agent Serving via Copy-on-Write Disaggregated KV Cache
by: Wang, Shao, et al.
Published: (2026)
by: Wang, Shao, et al.
Published: (2026)
SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
by: Lin, Zheng, et al.
Published: (2024)
by: Lin, Zheng, et al.
Published: (2024)
LoRA-C: Parameter-Efficient Fine-Tuning of Robust CNN for IoT Devices
by: Ding, Chuntao, et al.
Published: (2024)
by: Ding, Chuntao, et al.
Published: (2024)
Efficient Multi-Adapter LLM Serving via Cross-Model KV-Cache Reuse with Activated LoRA
by: Li, Allison, et al.
Published: (2025)
by: Li, Allison, et al.
Published: (2025)
Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems
by: Jaiswal, Shashwat, et al.
Published: (2025)
by: Jaiswal, Shashwat, et al.
Published: (2025)
InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models
by: Chen, Hongyu, et al.
Published: (2026)
by: Chen, Hongyu, et al.
Published: (2026)
CLLoRA: An Approach to Measure the Effects of the Context Length for LLM Fine-Tuning
by: Zhang, Ping, et al.
Published: (2025)
by: Zhang, Ping, et al.
Published: (2025)
Exploring Selective Layer Fine-Tuning in Federated Learning
by: Sun, Yuchang, et al.
Published: (2024)
by: Sun, Yuchang, et al.
Published: (2024)
Co-LoRA: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients
by: Seo, Minhyuk, et al.
Published: (2025)
by: Seo, Minhyuk, et al.
Published: (2025)
HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
by: Lin, Zheng, et al.
Published: (2025)
by: Lin, Zheng, et al.
Published: (2025)
Communication-Efficient Federated Fine-Tuning
by: Theologitis, Michael, et al.
Published: (2025)
by: Theologitis, Michael, et al.
Published: (2025)
EcoLoRA: Communication-Efficient Federated Fine-Tuning of Large Language Models
by: Liu, Han, et al.
Published: (2025)
by: Liu, Han, et al.
Published: (2025)
FedMoE-DA: Federated Mixture of Experts via Domain Aware Fine-grained Aggregation
by: Zhan, Ziwei, et al.
Published: (2024)
by: Zhan, Ziwei, et al.
Published: (2024)
Revisiting Federated Fine-Tuning: A Single Communication Round is Enough for Foundation Models
by: Wang, Ziyao, et al.
Published: (2024)
by: Wang, Ziyao, et al.
Published: (2024)
Topology-Aware Knowledge Propagation in Decentralized Learning
by: Sakarvadia, Mansi, et al.
Published: (2025)
by: Sakarvadia, Mansi, et al.
Published: (2025)
DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation
by: Xu, Jie, et al.
Published: (2024)
by: Xu, Jie, et al.
Published: (2024)
Similar Items
-
ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning
by: Wang, Xiaoyu, et al.
Published: (2025) -
pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023) -
Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA
by: Chen, Shuangyi, et al.
Published: (2024) -
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)