Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

30 papers of 6,984Sort Recent · Most cited
  1. 2025PDF ↗
  2. 2025
    The AI Hippocampus: How Far are We From Human Memory?Zixia Jia, Jiaqi Li, Yipeng Kang … Song-Chun ZhuTMLR
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  3. 2025PDF ↗
  4. 2025
    Memory-Modular Classification: Learning to Generalize with Memory ReplacementDahyun Kang, Ahmet İşcen, Eun-Byeol Jo … Cordelia SchmidTMLR
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  7. 2025
    Distributed Multi-Agent Lifelong LearningPrithviraj Tarale, Edward A. Rietman, Hava T. SiegelmannTMLR · University of Massachusetts Amherst
  8. 2025
    Efficient Few-Shot Continual Learning in Vision-Language ModelsA. Panos, Rahaf Aljundi, Daniel Olmeda Reino, Richard TurnerTMLR
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  10. 2025
    Class Incremental Learning from First Principles: A ReviewNeil Ashtekar, Jingxi Zhu, Vasant HonavarTMLR
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  14. 2025
    Uncertainty-Based Experience Replay for Task-Agnostic Continual Reinforcement LearningAdrian Remonda, Cole Terrell, Eduardo Veas, Marc MasanaTMLR
  15. 2025
    Hard-Negative Prototype-Based Regularization for Few-Shot Class-Incremental LearningSeongbeom Park, Hyunju Yun, Daewon Chae … Jinkyu KimTMLR
  16. 2025
    Rethinking Memory in Continual Learning: Beyond a Monolithic Store of the PastYaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert BifetTMLR
  17. 2025
    A unifying framework for generalised Bayesian online learning in non-stationary environmentsGerardo Duràn-Martín, Leandro Sánchez-Betancourt, Alexander Y. Shestopaloff, Kevin MurphyTMLR
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  18. 2025PDF ↗
  19. 2025
    Towards LifeSpan Cognitive SystemsYu Wang, Chi Han, Tongtong Wu … Julian McAuleyTMLR
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  20. 2025
    Buffer-based Gradient Projection for Continual Federated LearningShenghong Dai, Jy-yong Sohn, Yicong Chen … Kangwook LeeTMLR
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  21. 2025
    Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual LearningMohammadamin Banayeeanzade, Mahdi Soltanolkotabi, Mohammad RostamiTMLR
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  24. 2025
    Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental LearningNisha Lakshmana Raichur, Lucas Heublein, Tobias Feigl … Felix OttTMLR
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  25. 2025
    Continual Learning from Simulated Interactions via Multitask Prospective Rehearsal for Bionic Limb Behavior ModelingSharmita Dey, Benjamin Paassen, Sarath Ravindran Nair … Arndt F. SchillingTMLR
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  26. 2025
    GenOL: Generating Diverse Examples for Name-only Online LearningMinhyuk Seo, Seongwon Cho, Minjae Lee … Jonghyun ChoiTMLR
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  27. 2025PDF ↗
  28. 2025
    Personalized Negative Reservoir for Incremental Learning in Recommender SystemsAntonios Valkanas, Yuening Wang, Yingxue Zhang, Mark CoatesTMLR
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  29. 2025
    Investigating Continual Pretraining in Large Language Models: Insights and ImplicationsÇağatay Yıldız, Nishaanth Kanna Ravichandran, Sharma, Nitin … Beyza ErmişTMLR
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  30. 2025
    Metalearning Continual Learning AlgorithmsKazuki Irie, Róbert Csordás, Jürgen SchmidhuberTMLR
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.