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.

10 papers of 11,817Sort Recent · Most cited
  1. 2025
    Continual Learning of Large Language ModelsTongtong Wu, Thuy-Trang Vu, Linhao Luo, Gholamreza HaffariEMNLP
  2. 2024
    Towards LifeSpan Cognitive SystemsYu Wang, Chi Han, Tongtong Wu … Julian McAuleyTrans. Mach. Learn. Res.
    PDF ↗
  3. 2024
    Double Mixture: Towards Continual Event Detection from SpeechJingqi Kang, Tongtong Wu, Jinming Zhao … Gholamreza HaffariarXiv
    PDF ↗
  4. 2024
    Continual Learning for Large Language Models: A SurveyTongtong Wu, Linhao Luo, Yuan-Fang Li … Gholamreza HaffariarXiv
    PDF ↗
  5. 2023
    Active Continual Learning: On Balancing Knowledge Retention and LearnabilityThuy-Trang Vu, Shahram Khadivi, Mahsa Ghorbanali … Gholamreza HaffariApplied Informatics
    PDF ↗
  6. 2023
    Active Continual Learning: Labelling Queries in a Sequence of TasksThuy-Trang Vu, Shahram Khadivi, Dinh Q. Phung, Gholamreza HaffariarXiv
  7. 2022
    Pretrained Language Model in Continual Learning: A Comparative StudyTongtong Wu, Massimo Caccia, Zhuang Li … Gholamreza HaffariICLR
  8. 2021
    Curriculum-Meta Learning for Order-Robust Continual Relation ExtractionTongtong Wu, Xuekai Li, Yuan-Fang Li … Guoqiang XuAAAI · Southeast University · Monash University · +1
    PDF ↗
  9. 2021
    Total Recall: a Customized Continual Learning Method for Neural Semantic ParsersZhuang Li, Lizhen Qu, Gholamreza HaffariEMNLP · Monash University
    PDF ↗
  10. 2021
    Lifelong Explainer for Lifelong LearnersXuelin Situ, Sameen Maruf, Ingrid Zukerman … Gholamreza HaffariEMNLP · Monash University · Commonwealth Scientific and Industrial Research Organisation · +2
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.