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.

5 papers of 8,653Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2026
    Learning sculpts orthogonal task manifolds for continual skill learning in recurrent networksZihan Liu, Anno C. Kurth, Yuma Osako, Toshitake AsabukibioRxiv · Chinese University of Hong Kong · RIKEN Center for Brain Science · +2
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  3. 2021
    AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive SummarizationTiezheng Yu, Zihan Liu, Pascale FungNAACL · Hong Kong University of Science and Technology
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  4. 2021
    Preserving Cross-Linguality of Pre-trained Models via Continual LearningZihan Liu, Genta Indra Winata, Andrea Madotto, Pascale FungWorkshop on Representation Learning for NLP (RepL4NLP-2021) · Hong Kong University of Science and Technology
  5. 2020
    Exploring Fine-tuning Techniques for Pre-trained Cross-lingual Models via Continual LearningZihan Liu, Genta Indra Winata, Andrea Madotto, Pascale FungarXiv · Hong Kong University of Science and Technology
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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.