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.

7 papers of 8,653Sort Recent · Most cited
  1. 2024
    Adaptive Memory Replay for Continual LearningJames Seale Smith, Lazar Valkov, Shaunak Halbe … Leonid KarlinskyCVPR · IBM (United States) · Georgia Institute of Technology
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  2. 2022
    CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual LearningJames Seale Smith, Leonid Karlinsky, Vyshnavi Gutta … Zsolt KiraCVPR · Georgia Institute of Technology · IBM (United States) · +1
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  3. 2022
    In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit MemoryGeethan Karunaratne, Michael Hersche, J. Langeneager … Abbas RahimiESSCIRC 2022- IEEE 48th European Solid State Circuits Con… · ETH Zurich · IBM Research - Zurich · +2
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  4. 2021
  5. 2020
    Relationship Matters: Relation Guided Knowledge Transfer for Incremental Learning of Object DetectorsKandan Ramakrishnan, Rameswar Panda, Quanfu Fan … Rogério FerisCVPR · IBM (United States)
  6. 2018
    Learning to Learn without Forgetting By Maximizing Transfer and Minimizing InterferenceMatthew Riemer, Ignacio Cases, Robert Ajemian … Gerald TesauroICLR · IBM (United States) · Stanford University · +2
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  7. 2018
    HOUDINI: Lifelong Learning as Program SynthesisLazar Valkov, Dipak Chaudhari, Akash Srivastava … Swarat ChaudhuriNeurIPS · Indian Institute of Technology Bombay · IBM (United States) · +2
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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.