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.

13 papers of 11,817Sort Recent · Most cited
  1. 2025
    CADE: Continual Weakly-supervised Video Anomaly Detection with EnsemblesSatoshi Hashimoto, Tatsuya Konishi, Tomoya Kaichi … Mori KurokawaWACV
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  4. 2025
    Dynamic Adapter Tuning for Long-Tailed Class-Incremental LearningYanan Gu, Muli Yang, Xu Yang … Cheng DengWACV
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  7. 2025
    EvoCL: Continual Learning over Evolving DomainsVishnuprasadh Kumaravelu, P. Srijith, Sunil GuptaWACV
  8. 2025
    Towards Unbiased Continual Learning: Avoiding Forgetting in the Presence of Spurious CorrelationsGiacomo Capitani, Lorenzo Bonicelli, A. Porrello … Elisa FicarraWACV
  9. 2025
    AdaPrefix++: Integrating Adapters, Prefixes and Hypernetwork for Continual LearningSayanta Adhikari, Dupati Srikar Chandra, P. Srijith … Naoyuki OneoWACV
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  11. 2025
    Are Exemplar-Based Class Incremental Learning Models Victim of Black-Box Poison Attacks?Neeresh Kumar Perla, Md. Iqbal Hossain, Afia Sajeeda, Ming ShaoWACV
  12. 2025
    Self-Supervised Incremental Learning of Object Representations from Arbitrary Image SetsGeorge Leotescu, A. Popa, Diana Grigore … Pietro PeronaWACV
  13. 2025PDF ↗
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.