Saved in:
| Main Authors: | Feng, Zhi-Quan, Lin, Ying-Jia, Kao, Hung-Yu |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.01046 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
SC-LoRA: Balancing Efficient Fine-tuning and Knowledge Preservation via Subspace-Constrained LoRA
by: Luo, Minrui, et al.
Published: (2025)
by: Luo, Minrui, et al.
Published: (2025)
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models
by: Chen, Guanduo, et al.
Published: (2025)
by: Chen, Guanduo, et al.
Published: (2025)
Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
by: Li, Shiwei, et al.
Published: (2025)
by: Li, Shiwei, et al.
Published: (2025)
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)
Rethinking the Rank Threshold for LoRA Fine-Tuning
by: Park, Juneyoung
Published: (2026)
by: Park, Juneyoung
Published: (2026)
AlignGuard-LoRA: Alignment-Preserving Fine-Tuning via Fisher-Guided Decomposition and Riemannian-Geodesic Collision Regularization
by: Das, Amitava, et al.
Published: (2025)
by: Das, Amitava, et al.
Published: (2025)
CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization
by: Deng, Yanxia, et al.
Published: (2025)
by: Deng, Yanxia, et al.
Published: (2025)
LoRA-PAR: A Flexible Dual-System LoRA Partitioning Approach to Efficient LLM Fine-Tuning
by: Huang, Yining, et al.
Published: (2025)
by: Huang, Yining, et al.
Published: (2025)
The Impact of Initialization on LoRA Finetuning Dynamics
by: Hayou, Soufiane, et al.
Published: (2024)
by: Hayou, Soufiane, 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)
LoRA vs. Full Fine-Tuning: A Theoretical Perspective
by: Zindari, Ali, et al.
Published: (2026)
by: Zindari, Ali, et al.
Published: (2026)
PLoRA: Efficient LoRA Hyperparameter Tuning for Large Models
by: Yan, Minghao, et al.
Published: (2025)
by: Yan, Minghao, et al.
Published: (2025)
Exploring Gradient Subspaces: Addressing and Overcoming LoRA's Limitations in Federated Fine-Tuning of Large Language Models
by: Mahla, Navyansh, et al.
Published: (2024)
by: Mahla, Navyansh, 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)
FedLoRA-Optimizer: Federated LoRA Fine-Tuning with Global and Local Optimization in Heterogeneous Data Scenarios
by: Zhao, Jianzhe, et al.
Published: (2025)
by: Zhao, Jianzhe, et al.
Published: (2025)
Rethinking LoRA for Data Heterogeneous Federated Learning: Subspace and State Alignment
by: Peng, Hongyi, et al.
Published: (2026)
by: Peng, Hongyi, 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)
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
by: Zhang, Fangzhao, et al.
Published: (2024)
by: Zhang, Fangzhao, et al.
Published: (2024)
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)
Aletheia: Gradient-Guided Layer Selection for Efficient LoRA Fine-Tuning Across Architectures
by: Saket, Abdulmalek
Published: (2026)
by: Saket, Abdulmalek
Published: (2026)
MoE-Sieve: Routing-Guided LoRA for Efficient MoE Fine-Tuning
by: Manzoni, Andrea
Published: (2026)
by: Manzoni, Andrea
Published: (2026)
Shared LoRA Subspaces for almost Strict Continual Learning
by: Kaushik, Prakhar, et al.
Published: (2026)
by: Kaushik, Prakhar, et al.
Published: (2026)
Kron-LoRA: Hybrid Kronecker-LoRA Adapters for Scalable, Sustainable Fine-tuning
by: Shen, Yixin
Published: (2025)
by: Shen, Yixin
Published: (2025)
CopRA: A Progressive LoRA Training Strategy
by: Zhuang, Zhan, et al.
Published: (2024)
by: Zhuang, Zhan, et al.
Published: (2024)
pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023)
by: Yi, Liping, et al.
Published: (2023)
QuAILoRA: Quantization-Aware Initialization for LoRA
by: Lawton, Neal, et al.
Published: (2024)
by: Lawton, Neal, et al.
Published: (2024)
LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification
by: Haider, Md Akib, et al.
Published: (2026)
by: Haider, Md Akib, et al.
Published: (2026)
Parameter-Efficient Fine-Tuning for HAR: Integrating LoRA and QLoRA into Transformer Models
by: Seregina, Irina, et al.
Published: (2025)
by: Seregina, Irina, et al.
Published: (2025)
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
by: Sheng, Ying, et al.
Published: (2023)
by: Sheng, Ying, et al.
Published: (2023)
HRP: High-Rank Preheating for Superior LoRA Initialization
by: Chen, Yuzhu, et al.
Published: (2025)
by: Chen, Yuzhu, et al.
Published: (2025)
Run LoRA Run: Faster and Lighter LoRA Implementations
by: Cherniuk, Daria, et al.
Published: (2023)
by: Cherniuk, Daria, et al.
Published: (2023)
FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning
by: Yan, Peishen, et al.
Published: (2026)
by: Yan, Peishen, et al.
Published: (2026)
Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning
by: Chen, Xin, et al.
Published: (2025)
by: Chen, Xin, et al.
Published: (2025)
$α$-LoRA: Effective Fine-Tuning via Base Model Rescaling
by: Firdoussi, Aymane El, et al.
Published: (2025)
by: Firdoussi, Aymane El, et al.
Published: (2025)
How Relevance Emerges: Interpreting LoRA Fine-Tuning in Reranking LLMs
by: Nijasure, Atharva, et al.
Published: (2025)
by: Nijasure, Atharva, 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)
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)
Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models
by: Hsu, Chia-Yi, et al.
Published: (2024)
by: Hsu, Chia-Yi, et al.
Published: (2024)
Origin Tracer: A Method for Detecting LoRA Fine-Tuning Origins in LLMs
by: Liang, Hongyu, et al.
Published: (2025)
by: Liang, Hongyu, et al.
Published: (2025)
Similar Items
-
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement
by: Bian, Jieming, et al.
Published: (2024) -
SC-LoRA: Balancing Efficient Fine-tuning and Knowledge Preservation via Subspace-Constrained LoRA
by: Luo, Minrui, et al.
Published: (2025) -
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models
by: Chen, Guanduo, et al.
Published: (2025) -
Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
by: Li, Shiwei, et al.
Published: (2025) -
KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
by: Azimi, Rambod, et al.
Published: (2024)