Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

20 papers of 11,817Sort Recent · Most cited
  1. 2022
    Three types of incremental learningGido M. van de Ven, Tinne Tuytelaars, Andreas S. ToliasNature Machine Intelligence · Baylor College of Medicine · University of Cambridge · +2
  2. 2022
    Generative Negative Text Replay for Continual Vision-Language PretrainingShipeng Yan, Lanqing Hong, Hang Xu … Xuming HeECCV
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  3. 2022
    Continual evaluation for lifelong learning: Identifying the stability gapMatthias De Lange, Gido M. van de Ven, Tinne TuytelaarsICLR
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  4. 2022
    Continual Pre-Training Mitigates Forgetting in Language and VisionAndrea Cossu, Tinne Tuytelaars, Antonio Carta … Davide BacciuNeural Networks
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  5. 2020PDF ↗
  6. 2021
    Rehearsal revealed: The limits and merits of revisiting samples in continual learningEli Verwimp, Matthias De Lange, Tinne TuytelaarsICCV · KU Leuven
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  7. 2021
    Avalanche: an End-to-End Library for Continual LearningVincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu … Davide MaltoniCVPR · University of Pisa · University of Bologna · +12
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  8. 2021
    Ternary Feature Masks: zero-forgetting for task-incremental learningMarc Masana, Tinne Tuytelaars, Joost van de WeijerCVPR · Universitat Autònoma de Barcelona · Barcelona Supercomputing Center · +2
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  9. 2021
    New Insights on Reducing Abrupt Representation Change in Online Continual LearningLucas Caccia, Rahaf Aljundi, Nader Asadi … Eugene BelilovskyICLR
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  10. 2019
    A Continual Learning Survey: Defying Forgetting in Classification TasksMatthias Delange, Rahaf Aljundi, Marc Masana … Tinne TuytelaarsTPAMI · Computer Vision Center · Huawei Technologies (Canada)
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  11. 2020
    Automatic Recall Machines: Internal Replay, Continual Learning and the BrainXu Ji, João F. Henriques, Tinne Tuytelaars, Andrea VedaldiarXiv
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  12. 2020
    Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open ProblemMatthias De Lange, Xu Jia, Sarah Parisot … Tinne TuytelaarsCVPR · KU Leuven · Huawei Technologies (Sweden)
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  13. 2020
    More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental LearningYu Liu, Sarah Parisot, Greg Slabaugh … Tinne TuytelaarsSpringer LNCS · KU Leuven · Huawei Technologies (China) · +1
  14. 2020
    On the Exploration of Incremental Learning for Fine-grained Image RetrievalWei Chen, Yu Liu, Weiping Wang … Michael S. LewBMVC · Leiden University · KU Leuven · +1
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  15. 2019
    Online Continual Learning with Maximally Interfered RetrievalRahaf Aljundi, Lucas Caccia, Eugene Belilovsky … Tinne TuytelaarsarXiv · McGill University · Université de Montréal · +1
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  16. 2018
    Task-Free Continual LearningRahaf Aljundi, Klaas Kelchtermans, Tinne TuytelaarsCVPR · KU Leuven
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  17. 2018
    Selfless Sequential LearningRahaf Aljundi, Marcus Rohrbach, Tinne TuytelaarsICLR
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  18. 2017
    Memory Aware Synapses: Learning what (not) to forgetRahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny … Tinne TuytelaarsSpringer LNCS · IMEC · KU Leuven · +2
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  19. 2017
    Encoder Based Lifelong LearningAmal Rannen, Rahaf Aljundi, Matthew B. Blaschko, Tinne TuytelaarsICCV · IMEC · KU Leuven
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  20. 2016
    Expert Gate: Lifelong Learning with a Network of ExpertsRahaf Aljundi, Punarjay Chakravarty, Tinne TuytelaarsCVPR · IMEC
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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.