{"total":536,"rows":[{"id":"2106.06843","title":"Federated Learning on Non-IID Data: A Survey","created":"2021-06-12","cited_by_count":346,"area":null},{"id":"2110.01167","title":"Trustworthy AI: From Principles to Practices","created":"2021-10-04","cited_by_count":207,"area":null},{"id":"2111.08834","title":"Federated Learning for Smart Healthcare: A Survey","created":"2021-11-16","cited_by_count":184,"area":null},{"id":"2312.03718","title":"Large Language Models in Law: A Survey","created":"2023-11-26","cited_by_count":128,"area":null},{"id":"2402.06954","title":"OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning","created":"2024-02-10","cited_by_count":128,"area":null},{"id":"2112.02918","title":"When the Curious Abandon Honesty: Federated Learning Is Not Private","created":"2021-12-06","cited_by_count":127,"area":null},{"id":"2107.06641","title":"Trustworthy AI: A Computational Perspective","created":"2021-07-12","cited_by_count":93,"area":null},{"id":"2306.01603","title":"Decentralized Federated Learning: A Survey and Perspective","created":"2023-06-02","cited_by_count":86,"area":null},{"id":"2204.10836","title":"Federated Learning Enables Big Data for Rare Cancer Boundary Detection","created":"2022-04-22","cited_by_count":84,"area":null},{"id":"2109.12273","title":"FedProc: Prototypical Contrastive Federated Learning on Non-IID data","created":"2021-09-25","cited_by_count":81,"area":null},{"id":"2111.09278","title":"Differentially Private Federated Learning on Heterogeneous Data","created":"2021-11-17","cited_by_count":74,"area":null},{"id":"2106.13673","title":"Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy","created":"2021-06-25","cited_by_count":69,"area":null},{"id":"2104.14362","title":"From Distributed Machine Learning to Federated Learning: A Survey","created":"2021-04-29","cited_by_count":66,"area":null},{"id":"2209.06015","title":"Black-box Dataset Ownership Verification via Backdoor Watermarking","created":"2022-08-04","cited_by_count":65,"area":null},{"id":"2104.13417","title":"Towards Fair Federated Learning with Zero-Shot Data Augmentation","created":"2021-04-27","cited_by_count":64,"area":null},{"id":"2403.13101","title":"AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks","created":"2024-03-19","cited_by_count":64,"area":null},{"id":"2407.00952","title":"SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models","created":"2024-07-01","cited_by_count":62,"area":null},{"id":"2106.10207","title":"Distributed Deep Learning in Open Collaborations","created":"2021-06-18","cited_by_count":58,"area":null},{"id":"2111.09360","title":"Personalized Federated Learning through Local Memorization","created":"2021-11-17","cited_by_count":57,"area":null},{"id":"2101.06905","title":"Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation","created":"2021-01-18","cited_by_count":56,"area":null},{"id":"2101.07511","title":"Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge","created":"2021-01-19","cited_by_count":56,"area":null},{"id":"2202.04309","title":"Vertical Federated Learning: Challenges, Methodologies and Experiments","created":"2022-02-09","cited_by_count":55,"area":null},{"id":"2206.10206","title":"Personalized Subgraph Federated Learning","created":"2022-06-21","cited_by_count":54,"area":null},{"id":"2310.05077","title":"FedFed: Feature Distillation against Data Heterogeneity in Federated Learning","created":"2023-10-08","cited_by_count":54,"area":"distill"},{"id":"2204.05011","title":"FederatedScope: A Flexible Federated Learning Platform for Heterogeneity","created":"2022-04-11","cited_by_count":53,"area":null},{"id":"2306.09486","title":"FedMultimodal: A Benchmark For Multimodal Federated Learning","created":"2023-06-15","cited_by_count":51,"area":null},{"id":"2103.17150","title":"Federated Learning: A Signal Processing Perspective","created":"2021-03-31","cited_by_count":49,"area":null},{"id":"2201.01601","title":"FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients","created":"2022-01-05","cited_by_count":46,"area":null},{"id":"2206.03655","title":"pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning","created":"2022-06-08","cited_by_count":44,"area":null},{"id":"2107.12603","title":"Federated Learning Meets Natural Language Processing: A Survey","created":"2021-07-27","cited_by_count":43,"area":null},{"id":"2301.01299","title":"Recent Advances on Federated Learning: A Systematic Survey","created":"2023-01-03","cited_by_count":41,"area":null},{"id":"2311.07784","title":"A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks","created":"2023-11-13","cited_by_count":41,"area":null},{"id":"2312.17493","title":"Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning","created":"2023-12-29","cited_by_count":41,"area":null},{"id":"2206.07284","title":"A Survey on Gradient Inversion: Attacks, Defenses and Future Directions","created":"2022-06-15","cited_by_count":40,"area":null},{"id":"2307.09182","title":"Federated Learning for Computationally-Constrained Heterogeneous Devices: A Survey","created":"2023-07-18","cited_by_count":40,"area":null},{"id":"2102.04737","title":"Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication","created":"2021-02-09","cited_by_count":39,"area":null},{"id":"2106.03328","title":"Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning","created":"2021-06-07","cited_by_count":39,"area":null},{"id":"2111.08211","title":"FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning","created":"2021-11-16","cited_by_count":39,"area":null},{"id":"2109.13236","title":"FedIPR: Ownership Verification for Federated Deep Neural Network Models","created":"2021-09-27","cited_by_count":36,"area":"safety"},{"id":"2111.13394","title":"Non-IID data and Continual Learning processes in Federated Learning: A long road ahead","created":"2021-11-26","cited_by_count":36,"area":null},{"id":"2303.12233","title":"LOKI: Large-scale Data Reconstruction Attack against Federated Learning through Model Manipulation","created":"2023-03-21","cited_by_count":36,"area":null},{"id":"2208.10888","title":"Joint Privacy Enhancement and Quantization in Federated Learning","created":"2022-08-23","cited_by_count":35,"area":null},{"id":"2110.14153","title":"Differentially Private Federated Bayesian Optimization with Distributed Exploration","created":"2021-10-27","cited_by_count":32,"area":null},{"id":"2106.04405","title":"Federated Neural Collaborative Filtering","created":"2021-06-02","cited_by_count":30,"area":null},{"id":"2106.09779","title":"Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses","created":"2021-06-17","cited_by_count":30,"area":null},{"id":"2304.01829","title":"A Survey on Vertical Federated Learning: From a Layered Perspective","created":"2023-04-04","cited_by_count":30,"area":null},{"id":"2306.05131","title":"Conformal Prediction for Federated Uncertainty Quantification Under Label Shift","created":"2023-06-08","cited_by_count":29,"area":null},{"id":"2307.09619","title":"Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning","created":"2023-07-18","cited_by_count":29,"area":null},{"id":"2203.13789","title":"FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations","created":"2022-03-25","cited_by_count":27,"area":null},{"id":"2104.03008","title":"FedFace: Collaborative Learning of Face Recognition Model","created":"2021-04-07","cited_by_count":26,"area":null},{"id":"2203.06735","title":"Private Non-Convex Federated Learning Without a Trusted Server","created":"2022-03-13","cited_by_count":26,"area":null},{"id":"2306.14123","title":"Privacy and Fairness in Federated Learning: on the Perspective of Trade-off","created":"2023-06-25","cited_by_count":26,"area":null},{"id":"2106.13039","title":"Low-Latency Federated Learning over Wireless Channels with Differential Privacy","created":"2021-06-20","cited_by_count":25,"area":null},{"id":"2112.06872","title":"Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors","created":"2021-12-13","cited_by_count":25,"area":null},{"id":"2204.03529","title":"FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity","created":"2022-04-07","cited_by_count":25,"area":null},{"id":"2306.01334","title":"Federated Domain Generalization: A Survey","created":"2023-06-02","cited_by_count":25,"area":null},{"id":"2201.12433","title":"FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks","created":"2022-01-28","cited_by_count":24,"area":null},{"id":"2302.10637","title":"A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy","created":"2023-02-21","cited_by_count":24,"area":null},{"id":"2106.06579","title":"Federated Learning with Spiking Neural Networks","created":"2021-06-11","cited_by_count":23,"area":null},{"id":"2111.05326","title":"The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning","created":"2021-11-09","cited_by_count":23,"area":null},{"id":"2409.01128","title":"Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning","created":"2024-09-02","cited_by_count":23,"area":"diffusion"},{"id":"2201.11986","title":"Gradient Masked Averaging for Federated Learning","created":"2022-01-28","cited_by_count":22,"area":null},{"id":"2308.16375","title":"A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications","created":"2023-08-31","cited_by_count":22,"area":null},{"id":"2210.08285","title":"FedCross: Towards Accurate Federated Learning via Multi-Model Cross-Aggregation","created":"2022-10-15","cited_by_count":21,"area":null},{"id":"2307.00974","title":"Over-The-Air Federated Learning: Status Quo, Open Challenges, and Future Directions","created":"2023-07-03","cited_by_count":21,"area":null},{"id":"2105.07603","title":"EasyFL: A Low-code Federated Learning Platform For Dummies","created":"2021-05-17","cited_by_count":20,"area":null},{"id":"2202.03672","title":"APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning","created":"2022-02-08","cited_by_count":20,"area":null},{"id":"2204.01499","title":"FedRecAttack: Model Poisoning Attack to Federated Recommendation","created":"2022-04-01","cited_by_count":20,"area":null},{"id":"2304.07421","title":"Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition","created":"2023-04-14","cited_by_count":19,"area":null},{"id":"2405.03409","title":"LightTR: A Lightweight Framework for Federated Trajectory Recovery","created":"2024-05-06","cited_by_count":19,"area":null},{"id":"2304.09762","title":"Practical Differentially Private and Byzantine-resilient Federated Learning","created":"2023-04-15","cited_by_count":18,"area":null},{"id":"2112.03555","title":"FedDAG: Federated DAG Structure Learning","created":"2021-12-07","cited_by_count":17,"area":null},{"id":"2304.13407","title":"FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models","created":"2023-04-26","cited_by_count":17,"area":null},{"id":"2406.00569","title":"Redefining Contributions: Shapley-Driven Federated Learning","created":"2024-06-01","cited_by_count":17,"area":null},{"id":"2104.07468","title":"The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector","created":"2021-04-14","cited_by_count":16,"area":null},{"id":"2108.00365","title":"A Decentralized Federated Learning Framework via Committee Mechanism with Convergence Guarantee","created":"2021-08-01","cited_by_count":16,"area":null},{"id":"2108.00974","title":"Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges","created":"2021-08-02","cited_by_count":16,"area":null},{"id":"2301.01542","title":"Federated Learning for Data Streams","created":"2023-01-04","cited_by_count":16,"area":null},{"id":"2301.04017","title":"Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation","created":"2023-01-09","cited_by_count":16,"area":null},{"id":"2308.11841","title":"A Survey for Federated Learning Evaluations: Goals and Measures","created":"2023-08-23","cited_by_count":16,"area":null},{"id":"2403.14101","title":"Text-Enhanced Data-free Approach for Federated Class-Incremental Learning","created":"2024-03-21","cited_by_count":16,"area":null},{"id":"2201.11865","title":"FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients","created":"2022-01-28","cited_by_count":15,"area":null},{"id":"2308.05832","title":"FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks","created":"2023-08-10","cited_by_count":15,"area":null},{"id":"2309.11039","title":"Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems","created":"2023-09-20","cited_by_count":15,"area":null},{"id":"2507.07024","title":"FlexOlmo: Open Language Models for Flexible Data Use","created":"2025-07-09","cited_by_count":15,"area":"moe"},{"id":"2106.00275","title":"H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning","created":"2021-06-01","cited_by_count":14,"area":null},{"id":"2110.03469","title":"Federated Learning from Small Datasets","created":"2021-10-07","cited_by_count":14,"area":null},{"id":"2112.05120","title":"On Convergence of Federated Averaging Langevin Dynamics","created":"2021-12-09","cited_by_count":14,"area":null},{"id":"2202.09155","title":"PerFED-GAN: Personalized Federated Learning via Generative Adversarial Networks","created":"2022-02-18","cited_by_count":14,"area":null},{"id":"2207.09611","title":"Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directions","created":"2022-07-20","cited_by_count":14,"area":null},{"id":"2210.14664","title":"Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering","created":"2022-10-26","cited_by_count":14,"area":null},{"id":"2302.11051","title":"Fusion of Global and Local Knowledge for Personalized Federated Learning","created":"2023-02-21","cited_by_count":14,"area":null},{"id":"2303.04274","title":"Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning","created":"2023-03-07","cited_by_count":14,"area":null},{"id":"2305.06473","title":"Securing Distributed SGD against Gradient Leakage Threats","created":"2023-05-10","cited_by_count":14,"area":null},{"id":"2406.12844","title":"Synergizing Foundation Models and Federated Learning: A Survey","created":"2024-06-18","cited_by_count":14,"area":null},{"id":"2110.11775","title":"Federated Learning over Wireless IoT Networks with Optimized Communication and Resources","created":"2021-10-22","cited_by_count":13,"area":null},{"id":"2111.03396","title":"FedLess: Secure and Scalable Federated Learning Using Serverless Computing","created":"2021-11-05","cited_by_count":13,"area":null},{"id":"2204.06516","title":"Decentralized Collaborative Learning Framework for Next POI Recommendation","created":"2022-03-30","cited_by_count":13,"area":null},{"id":"2205.00107","title":"Bridging Differential Privacy and Byzantine-Robustness via Model Aggregation","created":"2022-04-29","cited_by_count":13,"area":null},{"id":"2211.15893","title":"Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise","created":"2022-11-29","cited_by_count":13,"area":null}],"next_cursor":"100"}