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.

5 papers of 11,817Sort Recent · Most cited
  1. 2026
    Memento: Personalized RAG-Style Long-Retention Data Scaling for META Ads RecommendationXiaoyu Chen, Ruichen Wang, Jieming Di … Sandeep PandeyarXiv
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  2. 2026PDF ↗
  3. 2023
    NEOLAF, an LLM-powered neural-symbolic cognitive architectureRichard Tong, C. Cao, Timothy Lee … Yu LuarXiv
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  4. 2022
    Task Formulation Matters When Learning Continually: A Case Study in Visual Question AnsweringMavina Nikandrou, Yu Lu, Alessandro Suglia … Verena RieserarXiv
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  5. 2021
    Continually Learning Self-Supervised Representations with Projected Functional RegularizationAlex Gomez-Villa, Bartłomiej Twardowski, Yu Lu … Joost van de WeijerCVPR · Universitat Autònoma de Barcelona · Tianjin University of Technology · +1
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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.