Federated Learning

AAAI 2024arXiv:2308.12305

#2

FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning

Haokun Chen, Yao Zhang, Denis Krompass et al.

federated learningfoundation model finetuningmulti-modal learningparameter-efficient finetuning+4

86

AAAI 2024arXiv:2312.05770

#3

FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update

Ji Liu, Juncheng Jia, Tianshi Che et al.

federated learningasynchronous trainingstatistical heterogeneitysystem heterogeneity+4

75

CVPR 2024arXiv:2404.18962

#4

An Aggregation-Free Federated Learning for Tackling Data Heterogeneity

Yuan Wang, Huazhu Fu, Renuga Kanagavelu et al.

67

ICML 2024arXiv:2312.06353

#5

Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes

Zhen Qin, Daoyuan Chen, Bingchen Qian et al.

federated learninglarge language modelsfull-parameter tuningzeroth-order optimization+3

61

ICLR 2025arXiv:2410.14803

#6

FedAS: Bridging Inconsistency in Personalized Federated Learning

Xiyuan Yang, Wenke Huang, Mang Ye

DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent

Taiyi Wang, Zhihao Wu, Jianheng Liu et al.

54

ICLR 2025arXiv:2410.01463

#8

Selective Aggregation for Low-Rank Adaptation in Federated Learning

Pengxin Guo, Shuang Zeng, Yanran Wang et al.

47

CVPR 2024arXiv:2403.00041

#9

Global and Local Prompts Cooperation via Optimal Transport for Federated Learning

Hongxia Li, Wei Huang, Jingya Wang et al.

46

CVPR 2024arXiv:2405.16585

#10

Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity

Yuhang Chen, Wenke Huang, Mang Ye

43

CVPR 2024arXiv:2403.05890

#11

Towards Efficient Replay in Federated Incremental Learning

Yichen Li, Qunwei Li, Haozhao Wang et al.

federated incremental learningcatastrophic forgettingdata heterogeneityreplay mechanisms+2

41

CVPR 2024arXiv:2201.03172

#12

Communication-Efficient Federated Learning with Accelerated Client Gradient

Geeho Kim, Jinkyu Kim, Bohyung Han

39

AAAI 2024arXiv:2211.07864

#13

Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning

Shangchao Su, Mingzhao Yang, Bin Li et al.

federated learningprompt tuningmulti-domain learningadaptive networks+4

38

AAAI 2024arXiv:2312.06290

#14

Exploiting Label Skews in Federated Learning with Model Concatenation

Yiqun Diao, Qinbin Li, Bingsheng He

federated learninglabel skewsmodel concatenationnon-iid data+3

37

CVPR 2024arXiv:2404.02478

#15

FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning

Rishub Tamirisa, Chulin Xie, Wenxuan Bao et al.

personalized federated learningclient data heterogeneityparameter selectionsubnetwork discovery+3

37

ICLR 2024arXiv:2301.09109

#16

Federated Recommendation with Additive Personalization

Zhiwei Li, Guodong Long, Tianyi Zhou

36

ICLR 2024arXiv:2306.16504

#17

Momentum Benefits Non-iid Federated Learning Simply and Provably

Ziheng Cheng, Xinmeng Huang, Pengfei Wu et al.

36

ICML 2024arXiv:2405.18890

#18

FedMut: Generalized Federated Learning via Stochastic Mutation

Ming Hu, Cao Yue, Anran Li et al.

Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization

Ziqing Fan, Shengchao Hu, Jiangchao Yao et al.

federated learningsharpness-aware minimizationloss landscape flatnessdata heterogeneity+3

33

CVPR 2024arXiv:2401.04928

#20

Relaxed Contrastive Learning for Federated Learning

Seonguk Seo, Jinkyu Kim, Geeho Kim et al.

33

ICLR 2024arXiv:2306.05515

#21

PeFLL: Personalized Federated Learning by Learning to Learn

Jonathan Scott, Hossein Zakerinia, Christoph Lampert

32

ICLR 2024arXiv:2402.15070

#22

Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting

Rong Dai, Yonggang Zhang, Ang Li et al.

32

CVPR 2024arXiv:2312.02567

#23

Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts

Jiayi Chen, Benteng Ma, Hengfei Cui et al.

federated learningactive learningmedical image analysisdomain shift+4

31

ICLR 2024arXiv:2201.02658

#24

Fair and Efficient Contribution Valuation for Vertical Federated Learning

Zhenan Fan, Huang Fang, Xinglu Wang et al.

vertical federated learningcontribution valuationshapley valuefeature-based federated learning+3

31

ICLR 2024arXiv:2401.15273

#25

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning

Chenyu Zhang, Han Wang, Aritra Mitra et al.

31

ICLR 2024arXiv:2308.04466

#26

Backdoor Federated Learning by Poisoning Backdoor-Critical Layers

Haomin Zhuang, Mingxian Yu, Hao Wang et al.

30

ECCV 2024arXiv:2407.05005

#27

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching

Yichen Li, Wenchao Xu, Haozhao Wang et al.

federated learningdomain-incremental learningknowledge matchingpersonalized federated learning+4

29

ICML 2024arXiv:2405.09771

#28

Harmonizing Generalization and Personalization in Federated Prompt Learning

Tianyu Cui, Hongxia Li, Jingya Wang et al.

federated prompt learningvision-language modelsdata heterogeneitylow-rank adaptation+4

28

AAAI 2024arXiv:2312.12263

#29

FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels

Authors: Jichang Li, Guanbin Li, Hui Cheng et al.

federated learningnoisy label filteringlabel noise distributiondata privacy preservation+3

27

ICLR 2024arXiv:2309.01289

#30

Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning

Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya Ezzeldin et al.

26

ICLR 2025arXiv:2404.08003

#31

Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis

Guangchen (Eric) Lan, Dong-Jun Han, Abolfazl Hashemi et al.

25

AAAI 2024arXiv:2312.06989

#32

Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks

Caridad Arroyo Arevalo, Sayedeh Leila Noorbakhsh, Yun Dong et al.

25

ICML 2024arXiv:2301.12379

#33

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering

Yongxin Guo, Xiaoying Tang, Tao Lin

federated learningdistribution shiftsrobust clusteringfeature distribution shift+4

25

ICLR 2024arXiv:2502.14205

#34

Accurate Forgetting for Heterogeneous Federated Continual Learning

Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang et al.

24

ICLR 2024arXiv:2402.07011

#35

FedImpro: Measuring and Improving Client Update in Federated Learning

Zhenheng Tang, Yonggang Zhang, Shaohuai Shi et al.

23

AAAI 2024arXiv:2312.12703

#36

Federated Learning with Extremely Noisy Clients via Negative Distillation

Yang Lu, Lin Chen, Yonggang Zhang et al.

federated learningnoisy label correctionknowledge distillationnegative distillation+4

ECCV 2024arXiv:2311.11227

#37

FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients

Shangchao Su, Bin Li, Xiangyang Xue

federated learningfoundation modelsheterogeneous clientstransformer-based models+3

CVPR 2024arXiv:2302.06637

#38

PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees

Chulin Xie, De-An Huang, Wenda Chu et al.

CVPR 2024arXiv:2403.15760

#39

An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning

Jianqing Zhang, Yang Liu, Yang Hua et al.

AAAI 2024arXiv:2403.16561

#40

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning

Xinyuan Ji, Zhaowei Zhu, Wei Xi et al.

federated learninglabel noiseheterogeneous datanoisy label learning+3

ICLR 2024arXiv:2312.15023

#41

Federated Q-Learning: Linear Regret Speedup with Low Communication Cost

Zhong Zheng, Fengyu Gao, Lingzhou Xue et al.

CVPR 2024arXiv:2311.18129

#42

Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices

Huancheng Chen, Haris Vikalo

CVPR 2024arXiv:2405.17876

#43

Decentralized Directed Collaboration for Personalized Federated Learning

Yingqi Liu, Yifan Shi, Qinglun Li et al.

CVPR 2024arXiv:2403.14101

#44

Text-Enhanced Data-free Approach for Federated Class-Incremental Learning

Minh-Tuan Tran, Trung Le, Xuan-May Le et al.

19

ICML 2024arXiv:2405.11525

#45

Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors

Chun-Yin Huang, Kartik Srinivas, Xin Zhang et al.

federated learningdecentralized learningdata heterogeneitymodel heterogeneity+4

19

ECCV 2024arXiv:2409.01128

#46

Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning

Jinglin Liang, Jin Zhong, Hanlin Gu et al.

federated continual learningcatastrophic forgettingdiffusion modelsdata replay+4

19

CVPR 2024arXiv:2403.14737

#47

FedMef: Towards Memory-efficient Federated Dynamic Pruning

Hong Huang, Weiming Zhuang, Chen Chen et al.

federated learningdynamic pruningmemory efficiencyactivation pruning+3

ECCV 2024arXiv:2312.01537

#48

Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents

Yuqi Jia, Saeed Vahidian, Jingwei Sun et al.

federated learningdataset distillationdeep generative modelsdata heterogeneity+4

CVPR 2024arXiv:2311.05304

#49

Data Valuation and Detections in Federated Learning

Wenqian Li, Shuran Fu, Fengrui Zhang et al.

ICLR 2025arXiv:2406.10630

#50

Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models

Rui Ye, Jingyi Chai, Xiangrui Liu et al.

federated learningsafety alignmentinstruction tuninglarge language models+3

ECCV 2024arXiv:2401.02094

#51

PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning

Haiyang Guo, Fei Zhu, Wenzhuo Liu et al.

CVPR 2024arXiv:2403.16398

#52

Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data

Xinting Liao, Weiming Liu, Chaochao Chen et al.

CVPR 2024arXiv:2312.16279

#53

Cloud-Device Collaborative Learning for Multimodal Large Language Models

Guanqun Wang, Jiaming Liu, Chenxuan Li et al.

ICLR 2024arXiv:2307.04942

#54

Benchmarking Algorithms for Federated Domain Generalization

Ruqi Bai, Saurabh Bagchi, David Inouye

ICLR 2024arXiv:2309.14675

#55

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler

Zilinghan Li, Pranshu Chaturvedi, Shilan He et al.

CVPR 2025arXiv:2306.09363

#56

A Simple Data Augmentation for Feature Distribution Skewed Federated Learning

Yunlu Yan, Huazhu Fu, Yuexiang Li et al.

CVPR 2025arXiv:2503.00908

#57

Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model

Ziyuan Yang, Yingyu Chen, Zhiwen Wang et al.

low-dose ct denoisingfederated learningphysics-informed hypernetworksmedical large language models+3

CVPR 2024arXiv:2403.15605

#58

Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization

Khiem Le, Tuan Long Ho, Cuong Do et al.

federated domain generalizationnormalization layersdomain shiftprivacy-preserving learning+3

AAAI 2024arXiv:2401.10272

#59

Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization

Yikang Wei, Yahong Han

AAAI 2025arXiv:2408.08931

#60

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach

Zhiwei Li, Guodong Long, Tianyi Zhou et al.

federated collaborative filteringvariational autoencoderprivacy-preserving recommendationpersonalized federated learning+3

AAAI 2024arXiv:2307.05358

#61

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

Sikai Bai, Shuaicheng Li, Weiming Zhuang et al.

federated semi-supervised learningdata distribution heterogeneitybi-level optimizationclient model regularization+4

ICLR 2025arXiv:2410.10114

#62

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models

Jun Luo, Chen Chen, Shandong Wu

AAAI 2025arXiv:2404.03702

#63

Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach

Qingxiang Liu, Sheng Sun, Yuxuan Liang et al.

federated learningspatio-temporal forecastingcontrastive learningsemantic alignment+3

CVPR 2024arXiv:2308.12532

#64

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning

Gihun Lee, Minchan Jeong, SangMook Kim et al.

AAAI 2025arXiv:2412.20200

#65

Federated Unlearning with Gradient Descent and Conflict Mitigation

Zibin Pan, Zhichao Wang, Chi Li et al.

federated learningfederated unlearningprivacy leakagegradient conflicts+3

ECCV 2024arXiv:2404.12467

#66

Towards Multi-modal Transformers in Federated Learning

Guangyu Sun, Matias Mendieta, Aritra Dutta et al.

CVPR 2025arXiv:2410.04810

#67

FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models

Haokun Chen, Hang Li, Yao Zhang et al.

federated learninglatent diffusion modelsdata heterogeneityone-shot learning+4

ICML 2024arXiv:2405.06822

#68

MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis

Luyuan Xie, Manqing Lin, Tianyu Luan et al.

federated learningmodel heterogeneityknowledge distillationmedical image classification+4

ICLR 2024arXiv:2404.09816

#69

FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity

Kai Yi, Nidham Gazagnadou, Peter Richtarik et al.

CVPR 2025arXiv:2502.20709

#70

Unlearning through Knowledge Overwriting: Reversible Federated Unlearning via Selective Sparse Adapter

Zhengyi Zhong, Weidong Bao, Ji Wang et al.

federated unlearningknowledge overwritingsparse adaptersprivacy-preserving learning+3

ICLR 2024arXiv:2306.11201

#71

Adaptive Federated Learning with Auto-Tuned Clients

Junhyung Lyle Kim, Mohammad Taha Toghani, Cesar Uribe et al.

AAAI 2024arXiv:2312.08648

#72

CLIP-Guided Federated Learning on Heterogeneity and Long-Tailed Data

Jiangming Shi, Shanshan Zheng, Xiangbo Yin et al.

ICML 2024arXiv:2404.08447

#73

Federated Optimization with Doubly Regularized Drift Correction

Xiaowen Jiang, Anton Rodomanov, Sebastian Stich

federated learningdistributed optimizationclient drifthessian similarity+1

AAAI 2024arXiv:2312.13306

#74

Towards Fair Graph Federated Learning via Incentive Mechanisms

12794 Chenglu Pan, Jiarong Xu, Yue Yu et al.

graph federated learningincentive mechanismsagent valuationgradient alignment+4

ECCV 2024arXiv:2301.12195

#75

BAFFLE: A Baseline of Backpropagation-Free Federated Learning

Haozhe Feng, Tianyu Pang, Chao Du et al.

ICLR 2024arXiv:2401.08977

#76

FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data

Zikai Xiao, Zihan Chen, Liyinglan Liu et al.

ICLR 2024arXiv:2306.05879

#77

FedWon: Triumphing Multi-domain Federated Learning Without Normalization

Weiming Zhuang, Lingjuan Lyu

AAAI 2024arXiv:2312.07165

#78

Language-Guided Transformer for Federated Multi-Label Classification

I-Jieh Liu, Ci-Siang Lin, Fu-En Yang et al.

ICML 2024arXiv:2407.18365

#79

FADAS: Towards Federated Adaptive Asynchronous Optimization

Yujia Wang, Shiqiang Wang, Songtao Lu et al.

federated learningadaptive optimizationasynchronous updatesstraggler clients+2

AAAI 2025arXiv:2501.11360

#80

Federated Learning with Sample-level Client Drift Mitigation

Haoran Xu, Jiaze Li, Wanyi Wu et al.

AAAI 2024arXiv:2312.13380

#81

Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity

Yiyue Chen, Haris Vikalo, Chianing Wang

federated learningquantizationself-supervised learningdata heterogeneity+4

CVPR 2024arXiv:2405.14873

#82

Federated Online Adaptation for Deep Stereo

Matteo Poggi, Fabio Tosi

ICML 2024arXiv:2405.14791

#83

Recurrent Early Exits for Federated Learning with Heterogeneous Clients

Royson Lee, Javier Fernandez-Marques, Xu Hu et al.

federated learningheterogeneous clientsearly exitstransformer architecture+4

ICML 2024arXiv:2402.12780

#84

Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates

Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui et al.

federated learningbyzantine robustnessclient subsamplingrobust aggregation+4

AAAI 2024arXiv:2305.05090

#85

Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts

Kun Jin, Tongxin Yin, Zhongzhu Chen et al.

federated learningdistribution shift mappingsperformative predictionmodel-dependent data shift+3

ICML 2024arXiv:2408.03215

#86

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

Shiwei Li, Wenchao Xu, Haozhao Wang et al.

federated learningcommunication efficiencymodel binarizationbinary model updates+3

ICLR 2025arXiv:2405.15861

#87

Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization

Zhe Li, Bicheng Ying, Zidong Liu et al.

ICML 2024arXiv:2405.09892

#88

Balancing Similarity and Complementarity for Federated Learning

Kunda Yan, Sen Cui, Abudukelimu Wuerkaixi et al.

federated learningstatistical heterogeneitynon-i.i.d. dataclient cooperation+3

CVPR 2025arXiv:2503.05657

#89

NoT: Federated Unlearning via Weight Negation

Yasser Khalil, Leo Maxime Brunswic, Soufiane Lamghari et al.

federated unlearningweight negationmodel perturbationprivacy compliance+3

AAAI 2024arXiv:2403.11803

#90

Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation

AAAI 2024arXiv:2312.05551

#91

Multi-Dimensional Fair Federated Learning

Cong Su, Guoxian Yu, Jun Wang et al.

federated learninggroup fairnessclient fairnessdifferential multipliers+3

AAAI 2024arXiv:2402.08578

#92

FedLF: Layer-Wise Fair Federated Learning

Zibin Pan, Chi Li, Fangchen Yu et al.

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing

Yongzhe Jia, Xuyun Zhang, Amin Beheshti et al.

federated learningedge computingparameter sharingmodel pruning+4

ICLR 2024arXiv:2306.03013

#94

FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning

Junyuan Zhang, Shuang Zeng, Miao Zhang et al.

Knowledge-Aware Parameter Coaching for Personalized Federated Learning

Mingjian Zhi, Yuanguo Bi, Wenchao Xu et al.

FedST: Federated Style Transfer Learning for Non-IID Image Segmentation

Boyuan Ma, Yin Xiang, Jing Tan et al.

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning

Kostadin Garov, Dimitar I. Dimitrov, Nikola Jovanović et al.

ICML 2024arXiv:2407.03247

#98

Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning

Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu et al.

federated learningmodel heterogeneityheterogeneous model aggregationproxy models+4

ICLR 2024arXiv:2308.11464

#99

Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning

Yun-Hin Chan, Rui Zhou, Running Zhao et al.

ICLR 2025arXiv:2407.03038

#100

Towards Federated RLHF with Aggregated Client Preference for LLMs

Feijie Wu, Xiaoze Liu, Haoyu Wang et al.

federated learningreinforcement learning human feedbacklarge language modelspreference heterogeneity+2

10