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.

6 papers of 11,817Sort Recent · Most cited
  1. 2022
    CIRCLE: continual repair across programming languagesWei Yuan, Quanjun Zhang, Tieke He … Hongzhi YinACM SIGSOFT International Symposium on Software Testing a… · The University of Queensland · Nanjing University · +1
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  2. 2019
    The Capstone Journey: Exploring Design, Delivery and Evaluation in an Undergraduate Management Discipline ContextHeather Stewart, Luke Houghton, Clare BurnsThe Qualitative Report · Griffith University
  3. 2019
    Multi-label classification via incremental clustering on an evolving data streamTien Thanh Nguyen, Truong Dang, Anh Vu Luong … John McCallPattern Recognition · Robert Gordon University · Griffith University
  4. 2019
    Multi-label classification via label correlation and first order feature dependance in a data streamTien Thanh Nguyen, Thi Thu Thuy Nguyen, Anh Vu Luong … Bela StantićPattern Recognition · Griffith University · Robert Gordon University · +1
  5. 2016
    Describing and learning of related parts based on latent structural model in big dataLei Liu, Xiao Bai, Huigang Zhang … Wenzhong TangNeurocomputing · Shantou University · Beihang University · +1
  6. 2015
    An incremental structured part model for object recognitionXiao Bai, Peng Ren, Huigang Zhang, Jun ZhouNeurocomputing · Beihang University · China University of Petroleum, East China · +1
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.