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.

6 papers of 8,653Sort Recent · Most cited
  1. 2024
    May the Forgetting Be with You: Alternate Replay for Learning with Noisy LabelsMonica Millunzi, Lorenzo Bonicelli, Angelo Porrello … Simone CalderaraBMVC
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  2. 2024
    CLIP with Generative Latent Replay: a Strong Baseline for Incremental LearningEmanuele Frascaroli, Aniello Panariello, Pietro Buzzega … Simone CalderaraBMVC
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  3. 2024
    An Attention-based Representation Distillation Baseline for Multi-Label Continual LearningMartin Menabue, Emanuele Frascaroli, M. Boschini … Simone CalderaraICML
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  4. 2024
    A Second-Order Perspective on Model Compositionality and Incremental LearningAngelo Porrello, Lorenzo Bonicelli, Pietro Buzzega … Rita CucchiaraICLR
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  5. 2024
    Semantic Residual Prompts for Continual LearningMartin Menabue, Emanuele Frascaroli, Matteo Boschini … Simone CalderaraECCV
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  6. 2024
    Saliency-driven Experience Replay for Continual LearningGiovanni Bellitto, Federica Proietto Salanitri, Matteo Pennisi … Concetto SpampinatoNeurIPS
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.