Saved in:
| Main Authors: | Seo, Minhyuk, Kim, Taeheon, Lee, Hankook, Choi, Jonghyun, Tuytelaars, Tinne |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.11024 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
by: Sheng, Ying, et al.
Published: (2023)
by: Sheng, Ying, et al.
Published: (2023)
pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023)
by: Yi, Liping, 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)
InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models
by: Chen, Hongyu, et al.
Published: (2026)
by: Chen, Hongyu, et al.
Published: (2026)
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)
Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems
by: Jaiswal, Shashwat, et al.
Published: (2025)
by: Jaiswal, Shashwat, et al.
Published: (2025)
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)
HAFLQ: Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization
by: Su, Yang, et al.
Published: (2024)
by: Su, Yang, 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)
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)
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)
Unlocking the Edge deployment and ondevice acceleration of multi-LoRA enabled one-for-all foundational LLM
by: Kodavanti, Sravanth, et al.
Published: (2026)
by: Kodavanti, Sravanth, et al.
Published: (2026)
Federated LoRA with Sparse Communication
by: Kuo, Kevin, et al.
Published: (2024)
by: Kuo, Kevin, 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)
Can LoRA Fusion Support Cross-Domain Tasks in Cloud-Edge Collaboration?
by: Wang, Yatong, et al.
Published: (2026)
by: Wang, Yatong, et al.
Published: (2026)
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-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)
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)
Predictive-LoRA: A Proactive and Fragmentation-Aware Serverless Inference System for LLMs
by: Ni, Yinan, et al.
Published: (2025)
by: Ni, Yinan, et al.
Published: (2025)
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)
LoRA-based Parameter-Efficient LLMs for Continuous Learning in Edge-based Malware Detection
by: Rondanini, Christian, et al.
Published: (2026)
by: Rondanini, Christian, et al.
Published: (2026)
CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference
by: Li, Suyi, et al.
Published: (2024)
by: Li, Suyi, et al.
Published: (2024)
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
by: Brüel-Gabrielsson, Rickard, et al.
Published: (2024)
by: Brüel-Gabrielsson, Rickard, et al.
Published: (2024)
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)
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients
by: Su, Shangchao, et al.
Published: (2023)
by: Su, Shangchao, et al.
Published: (2023)
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)
FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
by: Jhunjhunwala, Divyansh, et al.
Published: (2025)
by: Jhunjhunwala, Divyansh, 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)
Improving LoRA in Privacy-preserving Federated Learning
by: Sun, Youbang, et al.
Published: (2024)
by: Sun, Youbang, 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)
Stabilizing Decentralized Federated Fine-Tuning via Topology-Aware Alternating LoRA
by: Wang, Xiaoyu, et al.
Published: (2026)
by: Wang, Xiaoyu, et al.
Published: (2026)
GC-Fed: Gradient Centralized Federated Learning with Partial Client Participation
by: Seo, Jungwon, et al.
Published: (2025)
by: Seo, Jungwon, et al.
Published: (2025)
EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices
by: Shen, Zheyu, et al.
Published: (2025)
by: Shen, Zheyu, et al.
Published: (2025)
LobRA: Multi-tenant Fine-tuning over Heterogeneous Data
by: Lin, Sheng, et al.
Published: (2025)
by: Lin, Sheng, et al.
Published: (2025)
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)
Beyond Aggregation: Guiding Clients in Heterogeneous Federated Learning
by: Wang, Zijian, et al.
Published: (2025)
by: Wang, Zijian, et al.
Published: (2025)
Training Heterogeneous Client Models using Knowledge Distillation in Serverless Federated Learning
by: Chadha, Mohak, et al.
Published: (2024)
by: Chadha, Mohak, et al.
Published: (2024)
S2M3: Split-and-Share Multi-Modal Models for Distributed Multi-Task Inference on the Edge
by: Yoon, JinYi, et al.
Published: (2025)
by: Yoon, JinYi, et al.
Published: (2025)
An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning
by: Zhang, Jianqing, et al.
Published: (2024)
by: Zhang, Jianqing, et al.
Published: (2024)
Similar Items
-
ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads
by: Zuo, Jingwei, et al.
Published: (2026) -
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
by: Sheng, Ying, et al.
Published: (2023) -
pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023) -
SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA
by: Liu, Jianmin, et al.
Published: (2025) -
InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models
by: Chen, Hongyu, et al.
Published: (2026)