Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 5,456Sort Recent · Most cited
  1. 2025
    Adaptive Few-Shot Class-Incremental Learning via Latent Variable ModelsTameem AdelJournal of Artificial Intelligence Research · University of Cambridge
  2. 2024
    Similarity-Based Adaptation for Task-Aware and Task-Free Continual LearningTameem AdelJournal of Artificial Intelligence Research · National Physical Laboratory · University of Cambridge
  3. 2022
    Towards Continual Reinforcement Learning: A Review and PerspectivesKhimya Khetarpal, Matthew Riemer, Irina Rish, Doina PrecupJournal of Artificial Intelligence Research · Google DeepMind (United Kingdom) · McGill University · +2
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  4. 2022
    Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A SurveyDanielle SaundersJournal of Artificial Intelligence Research · South Bend Museum of Art
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  5. 2020
    Towards Knowledgeable Supervised Lifelong Learning SystemsDiana Benavides‐Prado, Yun Sing Koh, Patricia RiddleJournal of Artificial Intelligence Research · University of Auckland
  6. 2017
    Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot TransferMohammad Rostami, David Isele, Eric EatonJournal of Artificial Intelligence Research · California University of Pennsylvania
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written 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.