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.

4 papers of 8,653Sort Recent · Most cited
  1. 2024
    A Framework for Neurosymbolic Goal-Conditioned Continual Learning in Open World EnvironmentsPierrick Lorang, Shivam Goel, Yash Shukla … Matthias ScheutzIROS · Tufts University · AIT Austrian Institute of Technology GmbH
  2. 2024
    Rapid context inference in a thalamocortical model using recurrent neural networksWei‐Long Zheng, Zhongxuan Wu, Ali Hummos … Michael M. HalassaNature Communications · Shanghai Jiao Tong University · Massachusetts Institute of Technology · +3
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  3. 2024
    Adapting to the “Open World”: The Utility of Hybrid Hierarchical Reinforcement Learning and Symbolic PlanningPierrick Lorang, H. Horváth, Tobias Kietreiber … Matthias ScheutzICRA · Tufts University · TU Wien · +1
  4. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
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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.