Cover Image

Bi-LoRA: Efficient Sharpness-Aware Minimization for Fine-Tuning Large-Scale Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Yuhang, Li, Tao, Huang, Zhehao, Yang, Zuopeng, Huang, Xiaolin
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
by: Azimi, Rambod, et al.
Published: (2024)

Parameter-Efficient Fine-Tuning for HAR: Integrating LoRA and QLoRA into Transformer Models
by: Seregina, Irina, et al.
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)

Rethinking the Rank Threshold for LoRA Fine-Tuning
by: Park, Juneyoung
Published: (2026)

LoRAFusion: Efficient LoRA Fine-Tuning for LLMs
by: Zhu, Zhanda, et al.
Published: (2025)

FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning
by: Yan, Peishen, et al.
Published: (2026)

SC-LoRA: Balancing Efficient Fine-tuning and Knowledge Preservation via Subspace-Constrained LoRA
by: Luo, Minrui, et al.
Published: (2025)

mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs
by: Ye, Zhengmao, et al.
Published: (2023)

LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently
by: Zhang, Yuanhe, et al.
Published: (2025)

$α$-LoRA: Effective Fine-Tuning via Base Model Rescaling
by: Firdoussi, Aymane El, et al.
Published: (2025)

FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning
by: Bian, Jieming, et al.
Published: (2026)

R-LoRA: Randomized Multi-Head LoRA for Efficient Multi-Task Learning
by: Liu, Jinda, et al.
Published: (2025)

Kron-LoRA: Hybrid Kronecker-LoRA Adapters for Scalable, Sustainable Fine-tuning
by: Shen, Yixin
Published: (2025)

Hierarchical LoRA MoE for Efficient CTR Model Scaling
by: Zeng, Zhichen, et al.
Published: (2025)

Echo-LoRA: Parameter-Efficient Fine-Tuning via Cross-Layer Representation Injection
by: Peng, Yihang, et al.
Published: (2026)

A Survey on LoRA of Large Language Models
by: Mao, Yuren, et al.
Published: (2024)

Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning
by: Chen, Xin, 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)

Localized LoRA: A Structured Low-Rank Approximation for Efficient Fine-Tuning
by: Barazandeh, Babak, et al.
Published: (2025)

A Sensitivity-Driven Expert Allocation Method in LoRA-MoE for Efficient Fine-Tuning
by: Xu, Junzhou, et al.
Published: (2025)

TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts
by: Kunwar, Pradip, et al.
Published: (2025)

Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)

CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization
by: Deng, Yanxia, et al.
Published: (2025)

Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA
by: Yang, Nuocheng, et al.
Published: (2026)

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)

Origin Tracer: A Method for Detecting LoRA Fine-Tuning Origins in LLMs
by: Liang, Hongyu, et al.
Published: (2025)

ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads
by: Zuo, Jingwei, et al.
Published: (2026)

AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning
by: Chen, Ziye, et al.
Published: (2026)

Activated LoRA: Fine-tuned LLMs for Intrinsics
by: Greenewald, Kristjan, et al.
Published: (2025)

ALLoRA: Adaptive Learning Rate Mitigates LoRA Fatal Flaws
by: Huang, Hai, et al.
Published: (2024)

LoRA+: Efficient Low Rank Adaptation of Large Models
by: Hayou, Soufiane, et al.
Published: (2024)

DLP-LoRA: Efficient Task-Specific LoRA Fusion with a Dynamic, Lightweight Plugin for Large Language Models
by: Zhang, Yuxuan, et al.
Published: (2024)

Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models
by: Liu, Jin, et al.
Published: (2026)

LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing
by: Li, Wenbing, et al.
Published: (2025)

Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training
by: Zhang, Chengqian, et al.
Published: (2026)

Profiling LoRA/QLoRA Fine-Tuning Efficiency on Consumer GPUs: An RTX 4060 Case Study
by: Avinash, MSR
Published: (2025)

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs
by: Arabpour, Reza, et al.
Published: (2025)

Improving the Serving Performance of Multi-LoRA Large Language Models via Efficient LoRA and KV Cache Management
by: Zhang, Hang, et al.
Published: (2025)

LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
by: Li, Yanan, et al.
Published: (2025)

NaRA: Noise-Aware LoRA for Parameter-Efficient Fine-Tuning of Diffusion LLMs
by: Wang, Shuaidi, et al.
Published: (2026)