Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

5 papers of 8,653Sort Recent · Most cited
  1. 2023
    Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven ControlMinh Ngoc Luu, Minh-Duong Nguyen, Ebrahim Bedeer … Quoc‐Viet PhamIEEE Transactions · Hanoi University of Science and Technology · VinUniversity · +4
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  2. 2025
    SAFA: Handling Sparse and Scarce Data in Federated Learning With Accumulative LearningNguyen Nang Hung, Truong Thao Nguyen, Trong Nghia Hoang … Phi Le NguyenIEEE Transactions · Tokyo University of Science · Iketani Science and Technology Foundation · +5
  3. 2024
    Continual Relation Extraction via Sequential Multi-Task LearningThanh-Thien Le, Mạnh Hùng Nguyễn, Tung Nguyen … Thien Huu NguyenAAAI · VinUniversity · Hanoi University of Science and Technology · +2
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  4. 2022
    Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture ApproximationHoang Phan, Anh Phan Tuan, Son Nguyen … Khoat ThanSpringer LNCS · VinUniversity · Hanoi University of Science and Technology
  5. 2020
    Incremental Learning for Autonomous Navigation of Mobile Robots based on Deep Reinforcement LearningManh Luong, Cuong PhamJournal of Intelligent & Robotic Systems · VinUniversity · Posts and Telecommunications Institute of Technology
About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.