Awesome Data Heterogeneity

Key papers

• Federated Adversarial Domain Adaptation (2019)
  Xingchao Peng et al.
  10.99
• Better Generative Replay for Continual Federated Learning (2023)
  Daiqing Qi et al.
  8.60
• Federated Domain Generalization: A Survey (2023)
  Ying Li et al.
  7.59
• Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data (2021)
  Zilong Zhao et al.
  7.50
• When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions (2023)
  Weiming Zhuang et al.
  7.50
• FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models (2025)
  Hui Lin et al.
  7.44
• Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation (2023)
  Francesco Santini et al.
  7.01
• Knowledge Distillation for Federated Learning: a Practical Guide (2022)
  Alessio Mora et al.
  6.78
• On the Push-Based Asynchronous Federated Learning: A Bias-Correction Aggregation Approach (2026)
  Jiahui Bai et al.
  6.72
• Fair and efficient contribution valuation for vertical federated learning (2022)
  Zhenan Fan et al.
  6.39
• PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark (2023)
  Jianqing Zhang et al.
  5.86
• LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data (2025)
  Yuxin Zhang et al.
  5.84
• Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? (2021)
  Shuxiao Chen et al.
  5.72
• Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis (2024)
  Guangchen Lan et al.
  5.34
• Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications (2023)
  Francesco Cremonesi et al.
  5.30
• AFed: Algorithmic Fair Federated Learning (2025)
  Huiqiang Chen et al.
  5.18
• FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning (2025)
  Yanbing Zhou et al.
  5.18
• Federated Learning with Sample-level Client Drift Mitigation (2025)
  Haoran Xu et al.
  5.18
• Federated Transfer Learning with Differential Privacy (2024)
  Mengchu Li et al.
  5.02
• Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection (2024)
  Liangqi Yuan et al.
  4.90
• PM-MOE: Mixture of Experts on Private Model Parameters for Personalized Federated Learning (2025)
  Yu Feng et al.
  4.82
• Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks (2025)
  Shuai Wang et al.
  4.76
• A Two-Stage CAE-Based Federated Learning Framework for Efficient Jamming Detection in 5G Networks (2025)
  Samhita Kuili et al.
  4.76
• Decentralized Low-Rank Fine-Tuning of Large Language Models (2025)
  Sajjad Ghiasvand et al.
  4.76
• Federated Large Language Models: Current Progress and Future Directions (2024)
  Yuhang Yao et al.
  4.54
• QSplitFL: Capability Aware Deep Q-Learning for Optimal Split Point Selection in Split Federated Learning (2026)
  Nazmus Shakib Shadin et al.
  4.39
• FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching (2026)
  Haoran Zhang et al.
  4.39
• Compositional Generative Modeling from Decentralized Data (2026)
  Mashrur M. Morshed et al.
  4.39
• Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning (2026)
  Haengbok Chung et al.
  4.39
• MoE Enhanced Federated Learning for Spatiotemporal Prediction (2026)
  Zhehao Dai et al.
  4.39
• Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT (2025)
  Xiaohong Yang et al.
  4.36
• Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping (2023)
  Martin Pelikan et al.
  4.35
• FIRMA: FIbonacci Ring Model Aggregation for Privacy-preserving Federated Learning (2026)
  Rachid Hedjam
  4.33
• FederatedRSF : Federated Random Survival Forests for Partially Overlapping Medical Data (2026)
  Maryam Moradpour et al.
  4.33
• Separate Aggregation of Split Network for Personalized Federated Learning (2026)
  Yunseok Kang et al.
  4.33
• Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences (2026)
  Jabin Koo et al.
  4.33
• BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning (2024)
  Zhengyuan Jiang et al.
  4.30
• Efficient Deployment of Large Language Models on Resource-constrained Devices (2025)
  Zhiwei Yao et al.
  4.25
• Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation (2025)
  Xiaoxiao He et al.
  4.25
• Over-the-Air Fair Federated Learning via Multi-Objective Optimization (2025)
  Shayan Mohajer Hamidi et al.
  4.25
• SelfFed: Self-Supervised Federated Learning for Data Heterogeneity and Label Scarcity in Medical Images (2023)
  Sunder Ali Khowaja et al.
  4.18
• FedICT: Federated Multi-task Distillation for Multi-access Edge Computing (2023)
  Zhiyuan Wu et al.
  4.13
• Entropy-driven Fair and Effective Federated Learning (2023)
  Lin Wang et al.
  4.13
• Federated Learning for Heterogeneous Electronic Health Record Systems with Cost Effective Participant Selection (2024)
  Jiyoun Kim et al.
  4.13
• Federated Learning in Practice: Reflections and Projections (2024)
  Katharine Daly et al.
  4.08
• Floe: Federated Specialization for Real-Time LLM-SLM Inference (2026)
  Chunlin Tian et al.
  4.04
• Towards Federated RLHF with Aggregated Client Preference for LLMs (2024)
  Feijie Wu et al.
  3.92
• Machine Learning-Assisted Sustainable Remanufacturing, Reusing and Recycling for Lithium-ion Batteries (2024)
  Shengyu Tao
  3.86
• Ontology- and LLM-based Data Harmonization for Federated Learning in Healthcare (2025)
  Natallia Kokash and Lei Wang and Thomas H. Gillespie and Adam Belloum and Paola Grosso and Sara Quinney and Lang Li and Bernard de Bono
  3.81
• Federated Hierarchical Reinforcement Learning for Adaptive Traffic Signal Control (2025)
  Yongjie Fu et al.
  3.75
• Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligence (2025)
  Ratun Rahman
  3.75
• Enhancing Efficiency in Multidevice Federated Learning through Data Selection (2022)
  Fan Mo et al.
  3.71
• Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering (2022)
  Shahryar Zehtabi et al.
  3.71
• FedNoisy: Federated Noisy Label Learning Benchmark (2023)
  Siqi Liang et al.
  3.71
• FedRIR: Rethinking Information Representation in Federated Learning (2025)
  Yongqiang Huang et al.
  3.64
• Federated Continual Learning: Concepts, Challenges, and Solutions (2025)
  Parisa Hamedi et al.
  3.64
• Distributed Learning and Inference Systems: A Networking Perspective (2025)
  Hesham G. Moussa et al.
  3.59
• UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration (2025)
  Chung-ju Huang et al.
  3.59
• Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning (2025)
  Mingyuan Fan et al.
  3.59
• FedAlign: Federated Domain Generalization with Cross-Client Feature Alignment (2025)
  Sunny Gupta et al.
  3.59