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.

17 papers of 11,817Sort Recent · Most cited
  1. 2026
    Dual-Modal Contrastive Learning for Continual Generalized Category DiscoveryWei Jin, Nan-Nan Li, Chengcheng Yang … Kuo LiMathematics
  2. 2025
    A Transfer Learning Approach for Diverse Motion Augmentation Under Data ScarcityJunwon Yoon, Jeon-Seong Kang, Ha-Yoon Song … Jangho ParkMathematics
  3. 2025
  4. 2025PDF ↗
  5. 2025
  6. 2025
  7. 2025
    DIA-TSK: A Dynamic Incremental Adaptive Takagi–Sugeno–Kang Fuzzy ClassifierHao Chen, Chenhui Sha, Mingqing Jiao … B. QinMathematics
  8. 2025
  9. 2024
  10. 2024
    An FTwNB Shield: A Credit Risk Assessment Model for Data Uncertainty and Privacy ProtectionShaona Hua, Chunying Zhang, Guanghui Yang … Jing RenMathematics
  11. 2024
  12. 2023
  13. 2023
  14. 2023
  15. 2023
  16. 2022
    Using Domain Adaptation for Incremental SVM Classification of Drift DataJunya Tang, Kuo‐Yi Lin, Li LiMathematics · Tongji University
  17. 2021
    Latent-Insensitive Autoencoders for Anomaly Detection and Class-Incremental LearningMuhammad S. Battikh, Artem LenskiyMathematics · Al-Azhar University · Australian National University
    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.