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.

16 papers of 11,817Sort Recent · Most cited
  1. 2026
    MAny: Merge Anything for Multimodal Continual Instruction TuningZijian Gao, Wang-Wang Jia, Xingxing Zhang … Ke XuarXiv
    PDF ↗
  2. 2026
  3. 2025
    Continual Action Quality Assessment via Adaptive Manifold-Aligned Graph RegularizationKang-Lei Zhou, Qingyi Pan, Xingxing Zhang … Liyuan WangarXiv
    PDF ↗
  4. 2025
    Knowledge Memorization and Rumination for Pre-trained Model-based Class-Incremental LearningZijian Gao, Wang-Wang Jia, Xingxing Zhang … Huaimin WangCVPR
  5. 2025
    Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental LearningZijian Gao, Shanhao Han, Xingxing Zhang … Huai-Min WangAAAI
  6. 2025
    Advancing Prompt-Based Methods for Replay-Independent General Continual LearningZhiqi Kang, Liyuan Wang, Xingxing Zhang, Alahari KarteekICLR
    PDF ↗
  7. 2024PDF ↗
  8. 2024
    MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality AssessmentKang-Lei Zhou, Liyuan Wang, Xingxing Zhang … Xiaohui LiangECCV
    PDF ↗
  9. 2023PDF ↗
  10. 2023
    Towards a General Framework for Continual Learning with Pre-trainingLiyuan Wang, Jingyi Xie, Xingxing Zhang … Jun ZhuarXiv
    PDF ↗
  11. 2023PDF ↗
  12. 2023PDF ↗
  13. 2023
    Incorporating neuro-inspired adaptability for continual learning in artificial intelligenceLiyuan Wang, Xingxing Zhang, Qian Li … Yi ZhongNature Machine Intelligence
    PDF ↗
  14. 2023PDF ↗
  15. 2022
    CoSCL: Cooperation of Small Continual Learners is Stronger than a Big OneLiyuan Wang, Xingxing Zhang, Qian Li … Yi ZhongECCV
    PDF ↗
  16. 2022
    Memory Replay with Data Compression for Continual LearningLiyuan Wang, Xingxing Zhang, Kuo Yang … Jun ZhuICLR
    PDF ↗
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.