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.

10 papers of 11,817Sort Recent · Most cited
  1. 2025
    Incremental Learning Methodologies for Addressing Catastrophic Forgetting: Analysis and Experimental EvaluationMiquel Serra-Perello, Alberto OrtizJournal of Artificial Intelligence Research
  2. 2025
    Adaptive Few-Shot Class-Incremental Learning via Latent Variable ModelsTameem AdelJournal of Artificial Intelligence Research
  3. 2024
    CluMo: Cluster-based Modality Fusion Prompt for Continual Learning in Visual Question AnsweringYuliang Cai, Mohammad RostamiJournal of Artificial Intelligence Research
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  4. 2024
    Similarity-Based Adaptation for Task-Aware and Task-Free Continual LearningTameem AdelJournal of Artificial Intelligence Research
  5. 2021
    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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  6. 2022
    Efficient Learning of Interpretable Classification RulesBishwamittra Ghosh, Dmitry Malioutov, Kuldeep S. MeelJournal of Artificial Intelligence Research · National University of Singapore
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  7. 2021
    CoLLIE: Continual Learning of Language Grounding from Language-Image EmbeddingsGabriel Skantze, Bram WillemsenJournal of Artificial Intelligence Research · KTH Royal Institute of Technology
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  8. 2020
    MADRaS : Multi Agent Driving SimulatorAnirban Santara, Sohan Rudra, Sree Aditya Buridi … Balaraman RavindranJournal of Artificial Intelligence Research · Indian Institute of Technology Kharagpur · University of Alberta · +6
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  9. 2020
    Towards Knowledgeable Supervised Lifelong Learning SystemsDiana Benavides‐Prado, Yun Sing Koh, Patricia RiddleJournal of Artificial Intelligence Research · University of Auckland
  10. 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 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.