Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 6,984Sort Recent · Most cited
  1. 2026
    The organization of multiple motor memories.Daniel M. WolpertCurrent Opinion in Neurobiology · Allen Institute for Brain Science
  2. 2025
    Curriculum effects in multitask learning through the lens of contextual inference.Sabyasachi Shivkumar, Máté Lengyel, Daniel M. WolpertCurrent Opinion in Neurobiology · Allen Institute for Brain Science · Central European University · +1
  3. 2024
    Leveraging dendritic properties to advance machine learning and neuro-inspired computing.Michalis Pagkalos, Roman Makarov, Panayiota PoiraziCurrent Opinion in Neurobiology · University of Crete · Institute of Molecular Biology and Biotechnology · +2
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  4. 2023
    Signatures of task learning in neural representations.Harsha Gurnani, N. Alex Cayco-GajicCurrent Opinion in Neurobiology · Twitter (United States) · University of Washington · +3
  5. 2022
    Representational drift: Emerging theories for continual learning and experimental future directions.Laura Driscoll, Lea Duncker, Christopher D. HarveyCurrent Opinion in Neurobiology · Stanford University · Howard Hughes Medical Institute · +1
  6. 2021
    Stable continual learning through structured multiscale plasticity manifoldsPoonam Mishra, Rishikesh NarayananCurrent Opinion in Neurobiology · Indian Institute of Science Bangalore
  7. 2020
    Neural inhibition for continual learning and memoryHelen C. BarronCurrent Opinion in Neurobiology · John Radcliffe Hospital · University of Oxford · +3
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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.