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.

9 papers of 8,653Sort Recent · Most cited
  1. 2024
    Diffusion Soup: Model Merging for Text-to-Image Diffusion ModelsBenjamin Biggs, Arjun Seshadri, Yang Zou … Stefano SoattoECCV
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  2. 2023
    Training Data Protection with Compositional Diffusion ModelsAditya Golatkar, Alessandro Achille, Ashwin Swaminathan, Stefano SoattoarXiv
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  3. 2023
    À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable PromptingBenjamin Bowman, Alessandro Achille, Luca Zancato … Stefano SoattoCVPR
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  4. 2022
    Integral Continual Learning Along the Tangent Vector Field of TasksTian Yu Liu, Aditya Golatkar, Stefano Soatto, Alessandro AchillearXiv
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  5. 2022
    Task Adaptive Parameter Sharing for Multi-Task LearningMatthew Wallingford, Hao Li, Alessandro Achille … Stefano SoattoCVPR · University of Washington
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  6. 2020
    Incremental Meta-Learning via Indirect Discriminant AlignmentQing Liu, Orchid Majumder, Alessandro Achille … Stefano SoattoECCV · Johns Hopkins University · Amazon (Germany)
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  7. 2020
    Incremental Few-Shot Meta-learning via Indirect Discriminant AlignmentQing Liu, Orchid Majumder, Alessandro Achille … Stefano SoattoECCV · Johns Hopkins University · Amazon (United States)
  8. 2019
    Toward Understanding Catastrophic Forgetting in Continual LearningCuong V. Nguyen, Alessandro Achille, Michael Lam … Stefano SoattoarXiv
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  9. 2018
    Life-Long Disentangled Representation Learning with Cross-Domain Latent HomologiesAlessandro Achille, Tom Eccles, Löıc Matthey … Irina HigginsNeurIPS
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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.