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. 2025
    Noise-Tolerant Coreset-Based Class Incremental Continual LearningEdison Mucllari, Aswin Raghavan, Zachary DanielsarXiv
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  2. 2023
    Efficient Model Adaptation for Continual Learning at the EdgeZachary Daniels, Jun Hu, Michael Lomnitz … David ZhangarXiv
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  3. 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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  4. 2022
    System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy GamesIndranil Sur, Zachary Daniels, Abrar Rahman … Aswin RaghavanInternational Conference on AI-ML-Systems · SRI International · American University · +3
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  5. 2022
    Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2Zachary Daniels, Aswin Raghavan, Jesse Hostetler … Ajay DivakaranCoLLAs
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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. By default it shows the 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. The rest are one click away under “All papers”. 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.