{"total":147,"rows":[{"id":"2302.00487","title":"A Comprehensive Survey of Continual Learning: Theory, Method and Application","created":"2023-01-31","cited_by_count":872,"area":null},{"id":"2106.01085","title":"Online Coreset Selection for Rehearsal-based Continual Learning","created":"2021-06-02","cited_by_count":117,"area":null},{"id":"2106.03097","title":"Preservation of the Global Knowledge by Not-True Distillation in Federated Learning","created":"2021-06-06","cited_by_count":87,"area":null},{"id":"2306.01603","title":"Decentralized Federated Learning: A Survey and Perspective","created":"2023-06-02","cited_by_count":86,"area":null},{"id":"2307.09218","title":"A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning","created":"2023-07-16","cited_by_count":69,"area":null},{"id":"2303.06937","title":"TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation","created":"2023-03-13","cited_by_count":65,"area":null},{"id":"2109.11369","title":"Recent Advances of Continual Learning in Computer Vision: An Overview","created":"2021-09-23","cited_by_count":55,"area":null},{"id":"2302.13001","title":"Better Generative Replay for Continual Federated Learning","created":"2023-02-25","cited_by_count":55,"area":null},{"id":"2403.19211","title":"Dual-Personalizing Adapter for Federated Foundation Models","created":"2024-03-28","cited_by_count":55,"area":null},{"id":"2106.03027","title":"Model Zoo: A Growing \"Brain\" That Learns Continually","created":"2021-06-06","cited_by_count":54,"area":null},{"id":"2302.00903","title":"No One Left Behind: Real-World Federated Class-Incremental Learning","created":"2023-02-02","cited_by_count":53,"area":null},{"id":"2312.16475","title":"Federated Continual Learning via Knowledge Fusion: A Survey","created":"2023-12-27","cited_by_count":53,"area":null},{"id":"2109.04197","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","created":"2021-09-09","cited_by_count":42,"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":"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":"2205.13462","title":"FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction","created":"2022-05-26","cited_by_count":35,"area":null},{"id":"2403.05890","title":"Towards Efficient Replay in Federated Incremental Learning","created":"2024-03-09","cited_by_count":33,"area":null},{"id":"2105.13309","title":"Concept drift detection and adaptation for federated and continual learning","created":"2021-05-27","cited_by_count":32,"area":null},{"id":"2307.08925","title":"Integration of Large Language Models and Federated Learning","created":"2023-07-18","cited_by_count":31,"area":null},{"id":"2304.03626","title":"Asynchronous Federated Continual Learning","created":"2023-04-07","cited_by_count":29,"area":null},{"id":"2110.03331","title":"CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability","created":"2021-10-07","cited_by_count":28,"area":null},{"id":"2207.07730","title":"How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition","created":"2022-07-15","cited_by_count":27,"area":null},{"id":"2302.14307","title":"GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting","created":"2023-02-28","cited_by_count":27,"area":null},{"id":"2112.00734","title":"Personalized Federated Learning with Adaptive Batchnorm for Healthcare","created":"2021-12-01","cited_by_count":26,"area":null},{"id":"2112.13246","title":"Towards Federated Learning on Time-Evolving Heterogeneous Data","created":"2021-12-25","cited_by_count":23,"area":null},{"id":"2306.15347","title":"FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer","created":"2023-06-27","cited_by_count":23,"area":null},{"id":"2412.13840","title":"Unleashing the Power of Continual Learning on Non-Centralized Devices: A Survey","created":"2024-12-18","cited_by_count":23,"area":null},{"id":"2307.02435","title":"Exploring Continual Learning for Code Generation Models","created":"2023-07-05","cited_by_count":22,"area":null},{"id":"2410.17961","title":"Closed-form merging of parameter-efficient modules for Federated Continual Learning","created":"2024-10-23","cited_by_count":22,"area":null},{"id":"2309.01289","title":"Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning","created":"2023-09-03","cited_by_count":21,"area":null},{"id":"2407.05005","title":"Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching","created":"2024-07-06","cited_by_count":21,"area":null},{"id":"2207.09413","title":"SphereFed: Hyperspherical Federated Learning","created":"2022-07-19","cited_by_count":19,"area":null},{"id":"2401.02094","title":"PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning","created":"2024-01-04","cited_by_count":19,"area":null},{"id":"2103.01319","title":"Adversarial training in communication constrained federated learning","created":"2021-03-01","cited_by_count":17,"area":null},{"id":"2211.04862","title":"Domain-incremental Cardiac Image Segmentation with Style-oriented Replay and Domain-sensitive Feature Whitening","created":"2022-11-09","cited_by_count":16,"area":null},{"id":"2211.13579","title":"Knowledge-Aware Federated Active Learning with Non-IID Data","created":"2022-11-24","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":"2403.14101","title":"Text-Enhanced Data-free Approach for Federated Class-Incremental Learning","created":"2024-03-21","cited_by_count":16,"area":null},{"id":"2412.13779","title":"Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence","created":"2024-12-18","cited_by_count":15,"area":null},{"id":"2109.00150","title":"Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning","created":"2021-09-01","cited_by_count":14,"area":null},{"id":"2502.07059","title":"Federated Continual Learning: Concepts, Challenges, and Solutions","created":"2025-02-10","cited_by_count":13,"area":null},{"id":"2207.11759","title":"Spatial-Temporal Federated Learning for Lifelong Person Re-identification on Distributed Edges","created":"2022-07-24","cited_by_count":12,"area":null},{"id":"2307.04869","title":"Fed-CPrompt: Contrastive Prompt for Rehearsal-Free Federated Continual Learning","created":"2023-07-10","cited_by_count":12,"area":null},{"id":"2405.06784","title":"Open Challenges and Opportunities in Federated Foundation Models Towards Biomedical Healthcare","created":"2024-05-10","cited_by_count":12,"area":null},{"id":"2112.06511","title":"Ex-Model: Continual Learning from a Stream of Trained Models","created":"2021-12-13","cited_by_count":11,"area":null},{"id":"2202.11453","title":"Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization","created":"2022-02-23","cited_by_count":11,"area":null},{"id":"2502.14205","title":"Accurate Forgetting for Heterogeneous Federated Continual Learning","created":"2025-02-20","cited_by_count":11,"area":null},{"id":"2212.01738","title":"FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge","created":"2022-12-04","cited_by_count":10,"area":null},{"id":"2210.06101","title":"Federated Continual Learning for Text Classification via Selective Inter-client Transfer","created":"2022-10-12","cited_by_count":9,"area":null},{"id":"2304.05260","title":"Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning","created":"2023-04-11","cited_by_count":9,"area":null},{"id":"2404.00983","title":"Continual Learning for Smart City: A Survey","created":"2024-04-01","cited_by_count":9,"area":null},{"id":"2405.02685","title":"FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer","created":"2024-05-04","cited_by_count":9,"area":null},{"id":"2412.18355","title":"Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor","created":"2024-12-24","cited_by_count":9,"area":null},{"id":"2501.15356","title":"Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting","created":"2025-01-26","cited_by_count":9,"area":null},{"id":"2203.02108","title":"Continual Horizontal Federated Learning for Heterogeneous Data","created":"2022-03-04","cited_by_count":8,"area":null},{"id":"2306.05764","title":"Fair yet Asymptotically Equal Collaborative Learning","created":"2023-06-09","cited_by_count":8,"area":null},{"id":"2306.14245","title":"FedSampling: A Better Sampling Strategy for Federated Learning","created":"2023-06-25","cited_by_count":8,"area":null},{"id":"2403.01387","title":"A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications","created":"2024-03-03","cited_by_count":8,"area":null},{"id":"2505.00365","title":"SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices","created":"2025-05-01","cited_by_count":8,"area":null},{"id":"2209.00195","title":"To Store or Not? Online Data Selection for Federated Learning with Limited Storage","created":"2022-09-01","cited_by_count":7,"area":null},{"id":"2305.15591","title":"Lightweight Learner for Shared Knowledge Lifelong Learning","created":"2023-05-24","cited_by_count":7,"area":null},{"id":"2312.09881","title":"Dynamic Heterogeneous Federated Learning with Multi-Level Prototypes","created":"2023-12-15","cited_by_count":7,"area":null},{"id":"2202.03925","title":"Learnings from Federated Learning in the Real world","created":"2022-02-08","cited_by_count":6,"area":null},{"id":"2306.09970","title":"Continual Adaptation of Vision Transformers for Federated Learning","created":"2023-06-16","cited_by_count":6,"area":null},{"id":"2312.05966","title":"Fake It Till Make It: Federated Learning with Consensus-Oriented Generation","created":"2023-12-10","cited_by_count":6,"area":null},{"id":"2406.02447","title":"Federated Class-Incremental Learning with Hierarchical Generative Prototypes","created":"2024-06-04","cited_by_count":6,"area":null},{"id":"2410.18378","title":"Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual Learning","created":"2024-10-24","cited_by_count":6,"area":null},{"id":"2508.12213","title":"Towards Generalizable Human Activity Recognition: A Survey","created":"2025-08-17","cited_by_count":6,"area":null},{"id":"2201.05527","title":"Federated Continual Learning for Socially Aware Robotics","created":"2022-01-14","cited_by_count":5,"area":null},{"id":"2203.13321","title":"Addressing Client Drift in Federated Continual Learning with Adaptive Optimization","created":"2022-03-24","cited_by_count":5,"area":null},{"id":"2405.18925","title":"Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond","created":"2024-05-29","cited_by_count":5,"area":null},{"id":"2411.07959","title":"On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients","created":"2024-11-12","cited_by_count":5,"area":null},{"id":"2411.18919","title":"Federated Continual Graph Learning","created":"2024-11-28","cited_by_count":5,"area":null},{"id":"2501.08737","title":"Resource-Constrained Federated Continual Learning: What Does Matter?","created":"2025-01-15","cited_by_count":5,"area":null},{"id":"2203.08399","title":"Privacy-preserving Online AutoML for Domain-Specific Face Detection","created":"2022-03-16","cited_by_count":4,"area":null},{"id":"2210.15051","title":"Federated Continual Learning to Detect Accounting Anomalies in Financial Auditing","created":"2022-10-26","cited_by_count":4,"area":null},{"id":"2211.12292","title":"Exemplar-free Continual Learning of Vision Transformers via Gated Class-Attention and Cascaded Feature Drift Compensation","created":"2022-11-22","cited_by_count":4,"area":null},{"id":"2306.01431","title":"On Knowledge Editing in Federated Learning: Perspectives, Challenges, and Future Directions","created":"2023-06-02","cited_by_count":4,"area":null},{"id":"2307.00497","title":"Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory","created":"2023-07-02","cited_by_count":4,"area":null},{"id":"2309.17192","title":"A Survey of Incremental Transfer Learning: Combining Peer-to-Peer Federated Learning and Domain Incremental Learning for Multicenter Collaboration","created":"2023-09-29","cited_by_count":4,"area":null},{"id":"2312.13500","title":"Federated Continual Novel Class Learning","created":"2023-12-21","cited_by_count":4,"area":null},{"id":"2310.15054","title":"Coordinated Replay Sample Selection for Continual Federated Learning","created":"2023-10-23","cited_by_count":3,"area":null},{"id":"2311.12548","title":"Multi-Session Budget Optimization for Forward Auction-based Federated Learning","created":"2023-11-21","cited_by_count":3,"area":null},{"id":"2411.01916","title":"Masked Autoencoders are Parameter-Efficient Federated Continual Learners","created":"2024-11-04","cited_by_count":3,"area":null},{"id":"2412.01630","title":"Review of Mathematical Optimization in Federated Learning","created":"2024-12-02","cited_by_count":3,"area":null},{"id":"2503.18511","title":"Global Convergence of Continual Learning on Non-IID Data","created":"2025-03-24","cited_by_count":3,"area":null},{"id":"2505.12245","title":"AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data","created":"2025-05-18","cited_by_count":3,"area":null},{"id":"2202.00270","title":"Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching","created":"2022-02-01","cited_by_count":2,"area":null},{"id":"2303.15378","title":"CoDeC: Communication-Efficient Decentralized Continual Learning","created":"2023-03-27","cited_by_count":2,"area":null},{"id":"2407.20705","title":"PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning","created":"2024-07-30","cited_by_count":2,"area":null},{"id":"2410.03042","title":"FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning","created":"2024-10-03","cited_by_count":2,"area":null},{"id":"2411.01904","title":"FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework","created":"2024-11-04","cited_by_count":2,"area":null},{"id":"2412.18926","title":"Exemplar-condensed Federated Class-incremental Learning","created":"2024-12-25","cited_by_count":2,"area":null},{"id":"2501.04588","title":"Federated-Continual Dynamic Segmentation of Histopathology guided by Barlow Continuity","created":"2025-01-08","cited_by_count":2,"area":null},{"id":"2506.21036","title":"An Information-Theoretic Analysis for Federated Learning under Concept Drift","created":"2025-06-26","cited_by_count":2,"area":null},{"id":"2509.19674","title":"C^2Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning","created":"2025-09-24","cited_by_count":2,"area":null},{"id":"2509.23683","title":"Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning","created":"2025-09-28","cited_by_count":2,"area":null},{"id":"2210.02940","title":"Communication-Efficient and Drift-Robust Federated Learning via Elastic Net","created":"2022-10-06","cited_by_count":1,"area":null},{"id":"2306.03542","title":"Masked Autoencoders are Efficient Continual Federated Learners","created":"2023-06-06","cited_by_count":1,"area":null},{"id":"2310.07497","title":"Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven Control","created":"2023-10-11","cited_by_count":1,"area":null}],"next_cursor":"100"}