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.

11 papers of 8,653Sort Recent · Most cited
  1. 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
  2. 2024
    Adversarially Robust Continual Learning with Anti-Forgetting LossKoki Mukai, Soichiro Kumano, Nicolas Michel … Toshihiko YamasakiICIP · The University of Tokyo
  3. 2023
    Improving Plasticity in Online Continual Learning via Collaborative LearningMaorong Wang, Nicolas Michel, Ling Xiao, Toshihiko YamasakiCVPR · The University of Tokyo · Université Gustave Eiffel
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  4. 2023
    Continual Learning of LSTM Using Ant Colony OptimizationRikitaka Kinoyama, Nagar Anthel Venkatesh Suryanarayanan, Hitoshi IbaIEEE Congress on Evolutionary Computation (CEC) · The University of Tokyo
  5. 2023
    Efficient, continual, and generalized learning in the brain – neural mechanism of Mental Schema 2.0 –Takefumi Ohki, Naoto Kunii, Zenas C. ChaoReviews in the Neurosciences · The University of Tokyo
  6. 2022
    Edge Computation-in-Memory for In-situ Class-incremental Learning with Knowledge DistillationShinsei Yoshikiyo, Naoko Misawa, Chihiro Matsui, Ken TakeuchiIEEE International Symposium on Circuits and Systems (ISCAS) · Tokyo University of Information Sciences · The University of Tokyo
  7. 2021
    Statistical Mechanical Analysis of Catastrophic Forgetting in Continual Learning with Teacher and Student NetworksHaruka Asanuma, Shiro Takagi, Yoshihiro Nagano … Masato OkadaJournal of the Physical Society of Japan · The University of Tokyo · University of Tsukuba · +1
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  8. 2020
    Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic ForgettingZeke Xie, Fengxiang He, Shaopeng Fu … Masashi SugiyamaNeural Computation · RIKEN Center for Advanced Intelligence Project · The University of Tokyo · +1
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  9. 2021
    Object Recognition with Continual Open Set Domain Adaptation for Home RobotIkki Kishida, Hong Chen, Masaki Baba … Hideki NakayamaWACV · The University of Tokyo
  10. 2018
    Analysis of inner structure of VSF-NetworkYoshitsugu Kakemoto, Shinichi NakasukaIJCNN · The University of Tokyo
  11. 2016
    A Joint Many-Task Model: Growing a Neural Network for Multiple NLP TasksKazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, Richard SocherEMNLP · Salesforce (United States) · The University of Tokyo
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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.