While Low-Rank Adaptation (LoRA) has proven beneficial for efficiently fine-tuning large models, LoRA fine-tuned text-to-image diffusion models lack diversity in the generated images, as the model tends to copy data from the observed training samples. This effect becomes more pronounced at higher values of adapter strength and for adapters with higher ranks which are fine-tuned on smaller datasets. To address these challenges, we present FouRA, a novel low-rank method that learns projections in the Fourier domain along with learning a flexible input-dependent adapter rank selection strategy. Through extensive experiments and analysis, we show that FouRA successfully solves the problems related to data copying and distribution collapse while significantly improving the generated image quality. We demonstrate that FouRA enhances the generalization of fine-tuned models thanks to its adaptive rank selection. We further show that the learned projections in the frequency domain are decorrelated and prove effective when merging multiple adapters. While FouRA is motivated for vision tasks, we also demonstrate its merits for language tasks on the GLUE benchmark.
RDA: Robust Domain Adaptation via Fourier Adversarial Attacking
Singtel Cognitive and Artificial Intelligence Lab for Enterprises（Singtel企业认知与人工智能实验室）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）
Fourier Test-time Adaptation with Multi-level Consistency for Robust Classification
Shenzhen University（深圳大学）；Zhejiang University（浙江大学）；University of Leeds（利兹大学）；Shenzhen RayShape Medical Technology Co., Ltd（深圳瑞影医疗科技有限公司）；Nanjing Medical University（南京医科大学）；The Affiliated Suzhou Hospital of Nanjing Medical University（南京医科大学附属苏州医院）
Fourier Domain Adaptation for Traffic Light Detection in Adverse Weather
Manipal Institute of Technology（曼尼帕尔理工学院）；Manipal Academy of Higher Education（曼尼帕尔高等教育学院）；Wells Fargo International Solutions Private Limited（富国国际解决方案私人有限公司）
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation
Beihang University（北京航空航天大学）；Zhejiang Lab（之江实验室）；Singapore University of Technology and Design（新加坡科技设计大学）；BioMind Technology Center（BioMind技术中心）；Zhongguancun Laboratory（中关村实验室）
SAM-Based Building Change Detection with Distribution-Aware Fourier Adaptation and Edge-Constrained Warping
School of Information Science and Technology, Southwest Jiaotong University（西南交通大学信息科学与技术学院）；School of Computer Science, China University of Geosciences（中国地质大学计算机学院）；University of Extremadura（埃斯特雷马杜拉大学）
Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation
The Chinese University of Hong Kong（香港中文大学）；Shun Hing Institute of Advanced Engineering（信兴高等工程研究所）；National University of Singapore（新加坡国立大学）；NUSRI Suzhou（新加坡国立大学苏州研究院）；University College London（伦敦大学学院）；Wellcome/EPSRC Centre for Interventional and Surgical Sciences（维康/英国工程与自然科学研究委员会介入与外科科学中心）
Exploring Sparsity for Parameter Efficient Fine Tuning Using Wavelets for Vision
Dept. of Electrical and Electronics Engineering, Koç University（电子工程系，科奇大学）；Codeway AI Research（Codeway人工智能研究）；Dept. of Computer Engineering, Middle East Technical University（计算机工程系，中东技术大学）
该研究提出小波微调（WaveFT），利用权重矩阵小波域的稀疏更新实现细粒度参数控制，在视觉任务的参数高效微调方法中达最优，已纳入Hugging Face PEFT库。
Integrating Frequency-Domain Representations with Low-Rank Adaptation in Vision-Language Models
University of Maryland Baltimore County (UMBC)（马里兰大学巴尔的摩县分校）；Center for Real-time Distributed Sensing and Autonomy (CARDS)（实时分布式感知与自主中心）；DEVCOM Army Research Laboratory（DEVCOM陆军研究实验室）
From Adaptation to Generalization: Adaptive Visual Prompting for Medical Image Segmentation
Technical University of Munich（慕尼黑技术大学）；Korea University（韩国大学）；Kyung Hee University（庆熙大学）；Seoul National University of Science and Technology（首尔科学技术大学）
Anisotropic Fourier Features for Positional Encoding in Medical Imaging
Center of Digital Health, Berlin Institute of Health at Charité – Universitätsmedizin Berlin（柏林查理医院数字健康中心）；Charité – Universitätsmedizin Berlin（柏林查理医院大学医学中心）；Freie Universität Berlin（柏林自由大学）；Humboldt-Universität zu Berlin（柏林洪堡大学）
Frame2Freq: Spectral Adapters for Fine-Grained Video Understanding
Institute for Artificial Intelligence, University of Stuttgart（斯图加特大学人工智能研究所）；University Hospital Heidelberg, Diagnostic and Interventional Radiology（海德堡大学医院放射诊断与介入科）；Intelligent Assistive Systems Lab, University of Hildesheim（希尔德斯海姆大学智能辅助系统实验室）
Cross-Domain Transfer with Self-Supervised Spectral-Spatial Modeling for Hyperspectral Image Classification
Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences（泉州装备制造研究所、海西院、中国科学院）；Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences（福建物质结构研究所、中国科学院）；Liaoning Technical University（辽宁技术大学）；State Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences（区域与城市生态国家重点实验室、城市环境研究所、中国科学院）
