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. 2023
    Design principles for lifelong learning AI acceleratorsDhireesha Kudithipudi, Anurag Daram, Abdullah M. Zyarah … Benjamin R. EpsteinNature Electronics · The University of Texas at San Antonio · Sandia National Laboratories · +6
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  2. 2023
    A Comprehensive Empirical Evaluation on Online Continual LearningAlbin Soutif--Cormerais, Antonio Carta, Andrea Cossu … Hamed HematiICCV · Computer Vision Center · University of Pisa · +2
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  3. 2023
    Memory Population in Continual Learning via Outlier EliminationJulio Hurtado, Alain Raymond-Sáez, Vladimir Araujo … Davide BacciuICCV · University of Pisa · Pontificia Universidad Católica de Chile · +1
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  4. 2023
    A Simple Recipe to Meta-Learn Forward and Backward TransferEdoardo Cetin, Antonio Carta, Oya ÇeliktutanICCV · King's College School · University of Pisa
  5. 2023
    PIVOT: Prompting for Video Continual LearningAndrés Villa, Juan León Alcázar, Motasem Alfarra … Bernard GhanemCVPR · Pontificia Universidad Católica de Chile · King Abdullah University of Science and Technology · +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. 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.