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.

11 papers of 5,456Sort Recent · Most cited
  1. 2026
    DECODE: Domain-Aware Continual Domain Expansion for Motion PredictionBoqi Li, Haojie Zhu, Henry LiuTPAMI · University of Michigan
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  2. 2025
    Visuo-Tactile Class-Incremental LearningHao Fu, Fengyu Yang, Boyang Wang … Hui QianACM Transactions · Zhejiang University · Yale University · +3
  3. 2024
    Continual Relation Extraction via Sequential Multi-Task LearningThanh-Thien Le, Mạnh Hùng Nguyễn, Tung Nguyen … Thien Huu NguyenAAAI · VinUniversity · Hanoi University of Science and Technology · +2
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  4. 2024
    Effective Restoration of Source Knowledge in Continual Test Time AdaptationFahim Faisal Niloy, Sk Miraj Ahmed, Dripta S. Raychaudhuri … Amit K. Roy–ChowdhuryWACV · University of California, Riverside · University of Michigan
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  5. 2023
    Robustness-Preserving Lifelong Learning Via Dataset CondensationJinghan Jia, Yihua Zhang, Dogyoon Song … Alfred O. HeroICASSP · Michigan State University · University of Michigan
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  6. 2023
    A Domain-Agnostic Approach for Characterization of Lifelong Learning SystemsMegan M. Baker, Alexander New, Mario Aguilar-Simon … Gautam K. VallabhaNeural Networks · Johns Hopkins University Applied Physics Laboratory · Teledyne Technologies (United States) · +13
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  7. 2023
    Human Inspired Progressive Alignment and Comparative Learning for Grounded Word AcquisitionYuwei Bao, Barrett Lattimer, Joyce ChaiACL · University of Michigan
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  8. 2023
    Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part VDanai Koutra, Claudia Plant, Manuel Gomez-Rodriguez … Francesco BonchiSpringer LNCS · University of Michigan · University of Vienna · +2
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  9. 2021
    DANICE: Domain adaptation without forgetting in neural image compressionSudeep Katakol, Luis Herranz, Fei Yang, Marta MrakCVPR · University of Michigan · Umbo Computer Vision (United Kingdom) · +1
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  10. 2022
    How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of InterpolationEkdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. DickCoLLAs · University of Michigan
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  11. 2019
    Overcoming Catastrophic Forgetting With Unlabeled Data in the WildKibok Lee, Kimin Lee, Jinwoo Shin, Honglak LeeICCV · Korea Advanced Institute of Science and Technology · University of Michigan · +1
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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.