FedALT: Federated Fine-Tuning through Adaptive Local Training with Rest-of-World LoRA
Fuente:
arXiv
Saved in:
| Main Authors: | Bian, Jieming, Wang, Lei, Zhang, Letian, Xu, Jie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning
by: Bian, Jieming, et al.
Published: (2026)
by: Bian, Jieming, et al.
Published: (2026)
Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning
by: Wang, Lei, et al.
Published: (2025)
by: Wang, Lei, et al.
Published: (2025)
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement
by: Bian, Jieming, et al.
Published: (2024)
by: Bian, Jieming, et al.
Published: (2024)
FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning
by: Yan, Peishen, et al.
Published: (2026)
by: Yan, Peishen, et al.
Published: (2026)
KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
by: Azimi, Rambod, et al.
Published: (2024)
by: Azimi, Rambod, et al.
Published: (2024)
FedEL: Federated Elastic Learning for Heterogeneous Devices
by: Zhang, Letian, et al.
Published: (2025)
by: Zhang, Letian, et al.
Published: (2025)
Localized LoRA: A Structured Low-Rank Approximation for Efficient Fine-Tuning
by: Barazandeh, Babak, et al.
Published: (2025)
by: Barazandeh, Babak, 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)
HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
by: Tian, Chunlin, et al.
Published: (2024)
by: Tian, Chunlin, et al.
Published: (2024)
DR-LoRA: Dynamic Rank LoRA for Fine-Tuning Mixture-of-Experts Models
by: Deng, Guanzhi, et al.
Published: (2026)
by: Deng, Guanzhi, et al.
Published: (2026)
Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning
by: Kim, Myoungjun, et al.
Published: (2026)
by: Kim, Myoungjun, et al.
Published: (2026)
AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air
by: Yang, Shiyi, et al.
Published: (2025)
by: Yang, Shiyi, et al.
Published: (2025)
FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
by: Lee, Seanie, et al.
Published: (2025)
by: Lee, Seanie, et al.
Published: (2025)
MiCA Learns More Knowledge Than LoRA and Full Fine-Tuning
by: Rüdiger, Sten, et al.
Published: (2026)
by: Rüdiger, Sten, et al.
Published: (2026)
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
by: Li, Dengchun, et al.
Published: (2024)
by: Li, Dengchun, et al.
Published: (2024)
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)
LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging
by: Lee, Seungeon, et al.
Published: (2025)
by: Lee, Seungeon, et al.
Published: (2025)
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
by: Yen, Jui-Nan, et al.
Published: (2024)
by: Yen, Jui-Nan, et al.
Published: (2024)
LoRA-Squeeze: Simple and Effective Post-Tuning and In-Tuning Compression of LoRA Modules
by: Vulić, Ivan, et al.
Published: (2026)
by: Vulić, Ivan, et al.
Published: (2026)
Enhancing Aviation Communication Transcription: Fine-Tuning Distil-Whisper with LoRA
by: Mirzaei, Shokoufeh, et al.
Published: (2025)
by: Mirzaei, Shokoufeh, et al.
Published: (2025)
LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs
by: Arabpour, Reza, et al.
Published: (2025)
by: Arabpour, Reza, et al.
Published: (2025)
Mitigating Unintended Memorization with LoRA in Federated Learning for LLMs
by: Bossy, Thierry, et al.
Published: (2025)
by: Bossy, Thierry, et al.
Published: (2025)
A Note on LoRA
by: Fomenko, Vlad, et al.
Published: (2024)
by: Fomenko, Vlad, et al.
Published: (2024)
A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning
by: Bian, Jieming, et al.
Published: (2025)
by: Bian, Jieming, et al.
Published: (2025)
LoRA-Mini : Adaptation Matrices Decomposition and Selective Training
by: Singh, Ayush, et al.
Published: (2024)
by: Singh, Ayush, et al.
Published: (2024)
Rethinking the Rank Threshold for LoRA Fine-Tuning
by: Park, Juneyoung
Published: (2026)
by: Park, Juneyoung
Published: (2026)
Improving LoRA with Variational Learning
by: Cong, Bai, et al.
Published: (2025)
by: Cong, Bai, et al.
Published: (2025)
mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs
by: Ye, Zhengmao, et al.
Published: (2023)
by: Ye, Zhengmao, et al.
Published: (2023)
HypeLoRA: Hyper-Network-Generated LoRA Adapters for Calibrated Language Model Fine-Tuning
by: Trojan, Bartosz, et al.
Published: (2026)
by: Trojan, Bartosz, et al.
Published: (2026)
RadLite: Multi-Task LoRA Fine-Tuning of Small Language Models for CPU-Deployable Radiology AI
by: Gupta, Pankaj, et al.
Published: (2026)
by: Gupta, Pankaj, et al.
Published: (2026)
Text to Trust: Evaluating Fine-Tuning and LoRA Trade-offs in Language Models for Unfair Terms of Service Detection
by: Juttu, Noshitha Padma Pratyusha, et al.
Published: (2025)
by: Juttu, Noshitha Padma Pratyusha, et al.
Published: (2025)
A Survey on LoRA of Large Language Models
by: Mao, Yuren, et al.
Published: (2024)
by: Mao, Yuren, et al.
Published: (2024)
The Impact of Initialization on LoRA Finetuning Dynamics
by: Hayou, Soufiane, et al.
Published: (2024)
by: Hayou, Soufiane, et al.
Published: (2024)
LoRA Learns Less and Forgets Less
by: Biderman, Dan, et al.
Published: (2024)
by: Biderman, Dan, et al.
Published: (2024)
LoRA Is Slower Than You Think
by: Ko, Seokmin
Published: (2025)
by: Ko, Seokmin
Published: (2025)
Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning
by: Lee, Yu-Ang, et al.
Published: (2026)
by: Lee, Yu-Ang, et al.
Published: (2026)
DLP-LoRA: Efficient Task-Specific LoRA Fusion with a Dynamic, Lightweight Plugin for Large Language Models
by: Zhang, Yuxuan, et al.
Published: (2024)
by: Zhang, Yuxuan, et al.
Published: (2024)
FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA
by: Zhang, Haoran, et al.
Published: (2026)
by: Zhang, Haoran, et al.
Published: (2026)
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
by: Zhang, Jun, et al.
Published: (2025)
by: Zhang, Jun, et al.
Published: (2025)
Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA
by: Yang, Nuocheng, et al.
Published: (2026)
by: Yang, Nuocheng, et al.
Published: (2026)
Similar Items
-
FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning
by: Bian, Jieming, et al.
Published: (2026) -
Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning
by: Wang, Lei, et al.
Published: (2025) -
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement
by: Bian, Jieming, et al.
Published: (2024) -
FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning
by: Yan, Peishen, et al.
Published: (2026) -
KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
by: Azimi, Rambod, et al.
Published: (2024)