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.

7 papers of 11,817Sort Recent · Most cited
  1. 2025
    CASE-LoRA: Continual Adaptation with Structurally Evolving LoRA for Class-Incremental LearningDat Quang Mac, T. Thi, Tri-Thanh Nguyen, Quynh-Trang Pham ThiInternational Conference on Knowledge and Systems Enginee…
  2. 2025
    ELLA: Enhancing Long-Tailed Online Continual Learning with Layer AugmentationDinh-Nhat Loi, Tri-Thanh Nguyen, T. Dang, Quynh-Trang Pham ThiInternational Conference on Knowledge and Systems Enginee…
  3. 2025
    FDRL: Semantic-Aware Representation Learning with Feature Drift-Resistant Space RegularizationN. Nguyen, Tri-Thanh Nguyen, Quynh-Trang Pham ThiInternational Conference on Knowledge and Systems Enginee…
  4. 2025
    Enhanced Class Incremental Semantic Segmentation with Initial Model Pre-tuningVan-Truong Le, Quynh-Trang Pham Thi, Tri-Thanh Nguyen, T. DangInternational Conference on Multimedia Analysis and Patte…
  5. 2025
    CLM: Momentum and Torque Conservation for Robust Continual LearningThi-Phuong-Trang Pham, Van-Toan Phan, Xuan-Hung Ho, Tri-Thanh NguyenInternational Conference on Computational Collective Inte…
  6. 2025
    TMMP: Efficient Continual Learning via Mixture of LoRA Experts and Top Maximum Magnitude Parameter FusionQuynh-Trang Pham Thi, L. Phạm, Dinh-Dat Nguyen … T. DangAsian Conference on Intelligent Information and Database…
  7. 2025
    ZeroRFF: A Random Fourier Features and Analytic Learning Method for Generalized Class Incremental LearningDuc-Hung Nguyen, Tri-Thanh Nguyen, T. Dang, Quynh-Trang Pham ThiInternational Conference on Advanced Data Mining and Appl…
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.