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.

6 papers of 8,653Sort Recent · Most cited
  1. 2025
    Understanding the Limits of Lifelong Knowledge Editing in LLMsLukas Thede, Karsten Roth, Matthias Bethge … Hartvigsen, TomICML
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  2. 2024
    A Practitioner's Guide to Continual Multimodal PretrainingKarsten Roth, Vishaal Udandarao, Sebastian Dziadzio … Zeynep AkataarXiv
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  3. 2024
    Reflecting on the State of Rehearsal-free Continual Learning with Pretrained ModelsLukas Thede, Karsten Roth, Olivier J. Hénaff … Zeynep AkataCoLLAs
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  4. 2024
    Investigating Continual Pretraining in Large Language Models: Insights and ImplicationsÇağatay Yıldız, Nishaanth Kanna Ravichandran, Sharma, Nitin … Beyza ErmişTrans. Mach. Learn. Res.
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  5. 2023
    Infinite dSprites for Disentangled Continual Learning: Separating Memory Edits from GeneralizationSebastian Dziadzio, Çağatay Yıldız, Gido M. van de Ven … Matthias BethgeCoLLAs
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  6. 2023
    Continual Learning: Applications and the Road ForwardEli Verwimp, Rahaf Aljundi, Shai Ben-David … Gido M. van de VenTrans. Mach. Learn. Res.
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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.