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.

7 papers of 8,653Sort Recent · Most cited
  1. 2026
    BPG: Balancing Plasticity and Generalization for Domain Incremental LearningQiang Wang, Songlin Dong, Shaokun Wang … Yihong GongarXiv
    PDF ↗
  2. 2026
    StructAlign: Structured Cross-Modal Alignment for Continual Text-to-Video RetrievalShaokun Wang, Weili Guan, Jizhou Han … Liqiang NieSIGIR · Harbin Institute of Technology · Shenzhen Institute of Information Technology · +2
    PDF ↗
  3. 2026PDF ↗
  4. 2025
    Dynamic Integration of Task-Specific Adapters for Class Incremental LearningJiashuo Li, Shaokun Wang, Bo Qian … Yihong GongCVPR · Xi'an Jiaotong University
    PDF ↗
  5. 2024
    Non-exemplar Domain Incremental Learning via Cross-Domain Concept IntegrationQiang Wang, Yuhang He, Songlin Dong … Yihong GongECCV · Xi'an Jiaotong University
  6. 2023
    Non-Exemplar Class-Incremental Learning via Adaptive Old Class ReconstructionShaokun Wang, Weiwei Shi, Yuhang He … Yihong GongACM International Conference on Multimedia · Xi'an Jiaotong University · Xi'an University of Technology
    PDF ↗
  7. 2023
    Semantic Knowledge Guided Class-Incremental LearningShaokun Wang, Weiwei Shi, Songlin Dong … Yihong GongIEEE TCSVT · Xi'an Jiaotong University
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.