Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

76 papers of 4,574 · showing 1–50Sort Recent · Most cited
  1. 2026
    NeuMoSync: End‑to‑End Neuromodulatory Control for Plasticity and Adaptability in Continual LearningSeyed Roozbeh Razavi Rohani, Khashayar Khajavi, Wesley Chung … Mo ChenTMLR
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  2. 2026
    Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future DirectionsSarthak Kumar Maharana, Shambhavi Mishra, Yunbei Zhang … Yunhui GuoTMLR
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  3. 2026
    Amnesia: A Stealthy Replay Attack on Continual Learning DreamsAhmed Sharshar, Naveen Kumar Kummari, Mohsen GuizaniTMLR
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  4. 2026
    Theoretical Foundations of Continual Learning via Drift-Plus-PenaltyNazreen Shah, Govinda Arya, Bharath B. N., Ranjitha PrasadTMLR
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  5. 2025PDF ↗
  6. 2026
    CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual LearningAmirhosein Javadi, Tuomas Oikarinen, Tara Javidi, Tsui-Wei WengTMLR
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  7. 2026
    ARROW: Augmented Replay for RObust World modelsAbdulaziz Alyahya, Abdallah Al Siyabi, Markus Ernst … Gideon KowadloTMLR
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  8. 2025
    The AI Hippocampus: How Far are We From Human Memory?Zixia Jia, Jiaqi Li, Yipeng Kang … Song-Chun ZhuTMLR
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  9. 2026
    Forget Less, Retain More: A Lightweight Regularizer for Rehearsal-Based Continual LearningLama Alssum, Hasan Abed Al Kader Hammoud, Motasem Alfarra … Bernard GhanemTMLR
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  10. 2026
    Taming Modality Entanglement in Continual Audio-Visual SegmentationHong, Yuyang, Qi Yang, Tao Zhang … Shiming XiangTMLR
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  11. 2026
    Continually Adding New Languages to Multilingual Language ModelsAbraham Toluwase Owodunni, Sachin KumarTMLR
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  12. 2026PDF ↗
  13. 2026
    Holistic Continual Learning under Concept Drift with Adaptive Memory RealignmentAlif Ashrafee, Jedrzej Kozal, Micha l Woźniak, B. KrawczykTMLR
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  14. 2026PDF ↗
  15. 2026PDF ↗
  16. 2025PDF ↗
  17. 2026PDF ↗
  18. 2026
    Parameter Efficient Continual Learning with Dynamic Low-Rank AdaptationPrashant Bhat, Shakib Yazdani, Elahe Arani, Bahram ZonoozTMLR
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  19. 2026PDF ↗
  20. 2025
    Memory-Modular Classification: Learning to Generalize with Memory ReplacementDahyun Kang, Ahmet İşcen, Eun-Byeol Jo … Cordelia SchmidTMLR
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  21. 2025PDF ↗
  22. 2025PDF ↗
  23. 2026
    From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained HypergradientsNicolas Michel, Maorong Wang, Jiangpeng He, Toshihiko YamasakiTMLR
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  24. 2026
    Unlocking [CLS] Features for Continual Post-TrainingMurat Onur Yildirim, Elif Ceren Gok Yildirim, Joaquin VanschorenTMLR
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  25. 2025
    Efficient Few-Shot Continual Learning in Vision-Language ModelsA. Panos, Rahaf Aljundi, Daniel Olmeda Reino, Richard TurnerTMLR
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  26. 2026
    Modality-Inconsistent Continual Learning of Multimodal Large Language ModelsWeiguo Pian, Shijian Deng, Shentong Mo … Yapeng TianTMLR
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  27. 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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  28. 2026
    Continual Memorization of Factoids in Language ModelsHoward Chen, Jiayi Geng, Adithya Bhaskar … Danqi ChenTMLR
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  29. 2025PDF ↗
  30. 2026
    Privacy Leakage via Output Label Space and Differentially Private Continual LearningMarlon Tobaben, Alrawajfeh, Talal, Marcus Klasson … Antti HonkelaTMLR
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  31. 2025
    Towards LifeSpan Cognitive SystemsYu Wang, Chi Han, Tongtong Wu … Julian McAuleyTMLR
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  32. 2025
    Buffer-based Gradient Projection for Continual Federated LearningShenghong Dai, Jy-yong Sohn, Yicong Chen … Kangwook LeeTMLR
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  33. 2025
    Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual LearningMohammadamin Banayeeanzade, Mahdi Soltanolkotabi, Mohammad RostamiTMLR
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  34. 2025PDF ↗
  35. 2026
    Retrospective Feature Estimation for Continual LearningNghia D. Nguyen, Hieu Trung Nguyen, Ang Li … Khoa D. DoanTMLR
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  36. 2026PDF ↗
  37. 2026
    Federated Class-Incremental Learning with Hierarchical Generative PrototypesRiccardo Salami, Pietro Buzzega, Matteo Mosconi … Simone CalderaraTMLR
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  38. 2024
    AGALE: A Graph-Aware Continual Learning Evaluation FrameworkZhao, Tianqi, Hanjalic, Alan, Khosla, MeghaTMLR
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  39. 2025PDF ↗
  40. 2025
    Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental LearningNisha Lakshmana Raichur, Lucas Heublein, Tobias Feigl … Felix OttTMLR
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  41. 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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  42. 2024
    IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual LearningPrashant Bhat, Bharath Renjith, Elahe Arani, Bahram ZonoozTMLR
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  43. 2024PDF ↗
  44. 2024
    A Bag of Tricks for Few-Shot Class-Incremental LearningShuvendu Roy, Chunjong Park, Aldi Fahrezi, Ali EtemadTMLR
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  45. 2025
    GenOL: Generating Diverse Examples for Name-only Online LearningMinhyuk Seo, Seongwon Cho, Minjae Lee … Jonghyun ChoiTMLR
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  46. 2025PDF ↗
  47. 2024
    Simple and Scalable Strategies to Continually Pre-train Large Language ModelsAdam Ibrahim, Benjamin Therien, Kshitij Gupta … Irina RishTMLR
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  48. 2025
    Personalized Negative Reservoir for Incremental Learning in Recommender SystemsAntonios Valkanas, Yuening Wang, Yingxue Zhang, Mark CoatesTMLR
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  49. 2025
    Investigating Continual Pretraining in Large Language Models: Insights and ImplicationsÇağatay Yıldız, Nishaanth Kanna Ravichandran, Sharma, Nitin … Beyza ErmişTMLR
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  50. 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, and only papers with a PDF we can point you at, so every title opens the paper itself. 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.