Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

9 papers of 8,653Sort Recent · Most cited
  1. 2026
    CLIP-Based Class Incremental Semantic Segmentation Framework With Generalization-Preserving Knowledge DistillationQining Ren, Zhenyu Zhang, Depeng Li, Zhigang ZengIEEE TCSVT · Huazhong University of Science and Technology
  2. 2025
    Multiple semantic prompt for rehearsal-free continual learningJunwei Chen, Zhenyu Zhang, Depeng Li, Zhigang ZengNeural Networks · Huazhong University of Science and Technology
  3. 2025
    Complementary Learning Subnetworks Towards Parameter-Efficient Class-Incremental LearningDepeng Li, Zhigang Zeng, Wei Dai, Ponnuthurai Nagaratnam SuganthanTKDE · Huazhong University of Science and Technology · China University of Mining and Technology · +1
  4. 2025PDF ↗
  5. 2024PDF ↗
  6. 2024PDF ↗
  7. 2023
    Multi-View Class Incremental LearningDepeng Li, Tianqi Wang, Junwei Chen … Zhigang ZengInformation Fusion · National University of Singapore · Huazhong University of Science and Technology · +1
    PDF ↗
  8. 2023PDF ↗
  9. 2023
    CRNet: A Fast Continual Learning Framework With Random TheoryDepeng Li, Zhigang ZengTPAMI · Beijing Academy of Artificial Intelligence
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.