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.

3 papers of 8,653Sort Recent · Most cited
  1. 2026
    Degradation of Feature Space in Continual LearningChiara Lanza, Roberto Pereira, Marco Miozzo … Paolo DiniIEEE International Conference on Pervasive Computing and… · Artificial Intelligence Research Institute · IRIS Technology Solutions (Spain)
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  2. 2024
    An empirical evaluation of tinyML architectures for Class-Incremental Continual LearningMatteo Tremonti, Davide Dalle Pezze, Francesco Paissan … Gian Antonio SustoIEEE International Conference on Pervasive Computing and… · University of Padua · Fondazione Bruno Kessler
  3. 2022
    Federated Learning and catastrophic forgetting in pervasive computing: demonstration in HAR domainAnastasiia Usmanova, François Portet, Philippe Lalanda, Germán VegaIEEE International Conference on Pervasive Computing and… · Université Grenoble Alpes · Laboratoire d'Informatique de Grenoble · +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.