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.

15 papers of 8,653Sort Recent · Most cited
  1. 2025
    Joint Diffusion Models in Continual LearningPaweł Skierś, Kamil Rafał DejaICCV · Warsaw University of Technology · IDEA of Development Foundation
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  2. 2025
    Addressing The Devastating Effects Of Single-Task Data Poisoning In Exemplar-Free Continual LearningStanisław Pawlak, Bartłomiej Twardowski, T. P. Trzcinski, Joost van de WeijerarXiv · Warsaw University of Technology · Universitat Autònoma de Barcelona · +1
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  3. 2025
    Adapt & Align: Continual Learning with Generative Models Latent Space AlignmentKamil Rafał Deja, Bartosz Cywiński, Jan Rybarczyk, T. P. TrzcinskiNeurocomputing · Warsaw University of Technology · IDEA of Development Foundation · +1
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  4. 2025
    Exploring the Stability Gap in Continual Learning: The Role of the Classification HeadWojciech Łapacz, Daniel Marczak, Filip Szatkowski, T. P. TrzcinskiWACV · Warsaw University of Technology
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  5. 2025
    Variance-Covariance Regularization Improves Continual LearningPiotr Hondra, Daniel Marczak, Kamil Rafał DejaIEEE Access · Warsaw University of Technology
  6. 2024
    Category Adaptation Meets Projected Distillation in Generalized Continual Category DiscoveryGrzegorz Rypeść, Daniel Marczak, Sebastian Cygert … Bartłomiej TwardowskiECCV · Warsaw University of Technology · Gdańsk University of Technology · +1
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  7. 2024
    Divide and not forget: Ensemble of selectively trained experts in Continual LearningGrzegorz Rypeść, Sebastian Cygert, Valeriya Khan … Bartłomiej TwardowskiICLR · Warsaw University of Technology · Integrated Detector Electronics AS (Norway) · +6
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  8. 2023
    Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual LearningFilip Szatkowski, Mateusz Pyla, Marcin Przewięźlikowski … T. P. TrzcinskiICCV · Warsaw University of Technology · Integrated Detector Electronics AS (Norway) · +5
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  9. 2023
    Looking through the past: better knowledge retention for generative replay in continual learningValeriya Khan, Sebastian Cygert, Bartłomiej Twardowski, T. P. TrzcinskiICCV · Integrated Detector Electronics AS (Norway) · Corporación Universitaria de Colombia Ideas · +4
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  10. 2022
    Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual LearningKamil Rafał Deja, Paweł Wawrzyński, Wojciech Masarczyk … T. P. TrzcinskiIJCAI · Warsaw University of Technology · The University of Texas at Austin · +2
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  11. 2022
    Logarithmic Continual LearningWojciech Masarczyk, Paweł Wawrzyński, Daniel Marczak … T. P. TrzcinskiIEEE Access · Warsaw University of Technology · Jagiellonian University
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  12. 2021
    BinPlay: A Binary Latent Autoencoder for Generative Replay Continual LearningKamil Rafał Deja, Paweł Wawrzyński, Daniel Marczak … T. P. TrzcinskiIEEE International Joint Conference on Neural Network · Warsaw University of Technology
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  13. 2021
    On robustness of generative representations against catastrophic forgettingWojciech Masarczyk, Kamil Rafał Deja, T. P. TrzcinskiSpringer CCIS · Warsaw University of Technology · Jagiellonian University
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  14. 2021
    Continual Learning of 3D Point Cloud GeneratorsMichał Sadowski, Karol J. Piczak, Przemysław Spurek, T. P. TrzcinskiSpringer LNCS · Jagiellonian University · Warsaw University of Technology
  15. 2020
    Reducing catastrophic forgetting with learning on synthetic dataWojciech Masarczyk, Ivona TautkutėCVPR · Warsaw University of Technology · Institute of Theoretical and Applied Informatics · +3
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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.