A Sensitivity-Driven Expert Allocation Method in LoRA-MoE for Efficient Fine-Tuning
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Junzhou, Diao, Boyu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts
by: Kunwar, Pradip, et al.
Published: (2025)
by: Kunwar, Pradip, et al.
Published: (2025)
LoRALib: A Standardized Benchmark for Evaluating LoRA-MoE Methods
by: Wang, Shaoheng, et al.
Published: (2025)
by: Wang, Shaoheng, et al.
Published: (2025)
Hierarchical LoRA MoE for Efficient CTR Model Scaling
by: Zeng, Zhichen, et al.
Published: (2025)
by: Zeng, Zhichen, et al.
Published: (2025)
AT-MoE: Adaptive Task-planning Mixture of Experts via LoRA Approach
by: Li, Xurui, et al.
Published: (2024)
by: Li, Xurui, et al.
Published: (2024)
Adaptive and Fine-grained Module-wise Expert Pruning for Efficient LoRA-MoE Fine-Tuning
by: Li, Weihang, et al.
Published: (2026)
by: Li, Weihang, 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)
MoE-Sieve: Routing-Guided LoRA for Efficient MoE Fine-Tuning
by: Manzoni, Andrea
Published: (2026)
by: Manzoni, Andrea
Published: (2026)
Rethinking the Rank Threshold for LoRA Fine-Tuning
by: Park, Juneyoung
Published: (2026)
by: Park, Juneyoung
Published: (2026)
LoRAFusion: Efficient LoRA Fine-Tuning for LLMs
by: Zhu, Zhanda, et al.
Published: (2025)
by: Zhu, Zhanda, et al.
Published: (2025)
Noise-Robustness Through Noise: A Framework combining Asymmetric LoRA with Poisoning MoE
by: Wang, Zhaokun, et al.
Published: (2025)
by: Wang, Zhaokun, et al.
Published: (2025)
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)
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)
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)
ARD-LoRA: Dynamic Rank Allocation for Parameter-Efficient Fine-Tuning of Foundation Models with Heterogeneous Adaptation Needs
by: Shinwari, Haseeb Ullah Khan, et al.
Published: (2025)
by: Shinwari, Haseeb Ullah Khan, 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)
Echo-LoRA: Parameter-Efficient Fine-Tuning via Cross-Layer Representation Injection
by: Peng, Yihang, et al.
Published: (2026)
by: Peng, Yihang, et al.
Published: (2026)
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)
LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing
by: Li, Wenbing, et al.
Published: (2025)
by: Li, Wenbing, et al.
Published: (2025)
Kron-LoRA: Hybrid Kronecker-LoRA Adapters for Scalable, Sustainable Fine-tuning
by: Shen, Yixin
Published: (2025)
by: Shen, Yixin
Published: (2025)
On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs
by: Ye, Rongguang, et al.
Published: (2025)
by: Ye, Rongguang, et al.
Published: (2025)
Bi-LoRA: Efficient Sharpness-Aware Minimization for Fine-Tuning Large-Scale Models
by: Liu, Yuhang, et al.
Published: (2025)
by: Liu, Yuhang, 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)
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)
FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning
by: Yan, Peishen, et al.
Published: (2026)
by: Yan, Peishen, 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)
R-LoRA: Randomized Multi-Head LoRA for Efficient Multi-Task Learning
by: Liu, Jinda, et al.
Published: (2025)
by: Liu, Jinda, et al.
Published: (2025)
Towards Specialized Generalists: A Multi-Task MoE-LoRA Framework for Domain-Specific LLM Adaptation
by: Yang, Yuxin, et al.
Published: (2026)
by: Yang, Yuxin, et al.
Published: (2026)
Budgeted LoRA: Distillation as Structured Compute Allocation for Efficient Inference
by: Sabry, Mohammed, et al.
Published: (2026)
by: Sabry, Mohammed, et al.
Published: (2026)
Activated LoRA: Fine-tuned LLMs for Intrinsics
by: Greenewald, Kristjan, et al.
Published: (2025)
by: Greenewald, Kristjan, 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)
Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference
by: Liu, Baihui, et al.
Published: (2026)
by: Liu, Baihui, et al.
Published: (2026)
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)
Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training
by: Zhang, Chengqian, et al.
Published: (2026)
by: Zhang, Chengqian, et al.
Published: (2026)
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)
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)
Profiling LoRA/QLoRA Fine-Tuning Efficiency on Consumer GPUs: An RTX 4060 Case Study
by: Avinash, MSR
Published: (2025)
by: Avinash, MSR
Published: (2025)
MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
by: Jin, Peng, et al.
Published: (2024)
by: Jin, Peng, et al.
Published: (2024)
Retrieval-Augmented Mixture of LoRA Experts for Uploadable Machine Learning
by: Zhao, Ziyu, et al.
Published: (2024)
by: Zhao, Ziyu, et al.
Published: (2024)
FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge
by: Hu, Gang, et al.
Published: (2025)
by: Hu, Gang, et al.
Published: (2025)
Similar Items
-
TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts
by: Kunwar, Pradip, et al.
Published: (2025) -
LoRALib: A Standardized Benchmark for Evaluating LoRA-MoE Methods
by: Wang, Shaoheng, et al.
Published: (2025) -
Hierarchical LoRA MoE for Efficient CTR Model Scaling
by: Zeng, Zhichen, et al.
Published: (2025) -
AT-MoE: Adaptive Task-planning Mixture of Experts via LoRA Approach
by: Li, Xurui, et al.
Published: (2024) -
Adaptive and Fine-grained Module-wise Expert Pruning for Efficient LoRA-MoE Fine-Tuning
by: Li, Weihang, et al.
Published: (2026)