ResearchTrend.AI
Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach

Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach

Wei Dong
Xing Zhang
Bihui Chen
Dawei Yan
Zhijun Lin
Qingsen Yan
Peng Wang
Yang Yang
ArXiv (abs)PDFHTMLGithub (22★)

Papers citing "Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach"

6 / 6 papers shown
Title
Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning
Hasin Us Sami
Swapneel Sen
Amit K. Roy-Chowdhury
S. Krishnamurthy
Başak Güler
FedMLSILM
58
0
0
04 Jun 2025
APLA: A Simple Adaptation Method for Vision Transformers
APLA: A Simple Adaptation Method for Vision Transformers
Moein Sorkhei
Emir Konuk
Kevin Smith
Christos Matsoukas
133
0
0
14 Mar 2025
Mixture of Physical Priors Adapter for Parameter-Efficient Fine-Tuning
Mixture of Physical Priors Adapter for Parameter-Efficient Fine-Tuning
Zehua Wang
C. J. Li
QiXiang Ye
Tong Zhang
MoE
127
1
0
03 Dec 2024
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
Wei Dong
Yuan Sun
Yiting Yang
Xing Zhang
Zhijun Lin
Qingsen Yan
Han Zhang
Peng Wang
Yang Yang
Hengtao Shen
74
1
0
30 Oct 2024
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization
Yao Ni
Shan Zhang
Piotr Koniusz
459
8
0
25 Sep 2024
Multiple-Exit Tuning: Towards Inference-Efficient Adaptation for Vision Transformer
Multiple-Exit Tuning: Towards Inference-Efficient Adaptation for Vision Transformer
Zheng Liu
Jinchao Zhu
Nannan Li
Gao Huang
81
0
0
21 Sep 2024

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.