Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

28 papers of 11,817Sort Recent · Most cited
  1. 2026
    A negative-anchored self-relabeling strategy for multi-label class-incremental learningKaile Du, Junzhou Xie, Fan Lyu … Guangcan LiuNeurocomputing
  2. 2026
    A scalable complexity-regularized modular network for continual learningZi-Ye Fang, Bo Wan, Shang-Qi Guo, Jian K. LiuNeurocomputing
  3. 2026
    CD-IMM: A Bayesian non-parametric classifier for continual learningDaniele Castellana, Antonio CartaNeurocomputing
  4. 2026
    HiCPS: Hierarchical complementary prompt synergy for few-shot class-incremental learningQiang Huang, Sheng-Li Wu, Shaohua Wan … Hu LuNeurocomputing
  5. 2026
    Reducing catastrophic forgetting via gradient-based task organization in class-incremental learningJun-Long Huang, Ling-Ji Xu, Yining Liu, Zheng-Lin LiNeurocomputing
  6. 2026
    Geometry-controlled convex hull prototype framework for online task-free continual learningCong Tu Tran, Thanh Tuan Nguyen, T. Nguyen, Nadège Thirion-MoreauNeurocomputing
  7. 2026
    Towards self-adaptive learning: A comprehensive survey on continual learning under harsh conditionsR. Razavi-Far, Ehsan Hallaji, Alireza Fathalizadeh … Mohammad RostamiNeurocomputing
  8. 2026
  9. 2026
  10. 2026
    Knowledge consolidation with evolutionary alignment for class-incremental learningTung Tran, Marko Zolo Gozano Untalan, Zikang Wan, Danilo Vasconcellos VargasNeurocomputing
  11. 2026
  12. 2026
    Adapting to dissimilar tasks for continual learning via gradient norm regularisationXulong Wang, Tong Liu, Menghui Zhou … Po YangNeurocomputing
  13. 2026
  14. 2026
  15. 2026
    A practical guide to streaming continual learningAndrea Cossu, Federico Giannini, Giacomo Ziffer … Davide BacciuNeurocomputing
    PDF ↗
  16. 2026
  17. 2026
    Federated continual learning meets digital twins: A survey on methods, intersections and perspectivesMartina Savoia, Daniela Annunziata, Dipanwita Thakur … Francesco PiccialliNeurocomputing
  18. 2026
  19. 2026
    FedCapD: Federated class-incremental learning via capsule distillation and diffusion replaySaeed Iqbal, Muhammad Attique Khan, Ghulam Mustafa … Amir HussainNeurocomputing
  20. 2026
    Class-incremental continual graph learning with adversarial graph condensationQiao Yuan, Boxuan Zhu, Steven Guan … Prudence WongNeurocomputing
  21. 2026PDF ↗
  22. 2026
  23. 2026
  24. 2026
    Drift-aware variational autoencoder-based anomaly detection with two-level ensemblingJin Li, Kleanthis Malialis, Christos G. Panayiotou, Marios M. PolycarpouNeurocomputing
    PDF ↗
  25. 2026
  26. 2026
  27. 2026
  28. 2026
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.