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.

15 papers of 11,817Sort Recent · Most cited
  1. 2022
    A soft nearest-neighbor framework for continual semi-supervised learningZhiqi Kang, Enrico Fini, Moin Nabi … Karteek AlahariICCV · Institut national de recherche en sciences et technologies du numérique · University of Trento · +2
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  2. 2022
    Continual Learning from Demonstration of Robotic SkillsSayantan Auddy, Jakob Hollenstein, Matteo Saveriano … Justus PiaterRobotics and Autonomous Systems · Universität Innsbruck · University of Trento
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  3. 2021
    Generalising via Meta-Examples for Continual Learning in the WildAlessia Bertugli, Stefano Vincenzi, Simone Calderara, Andrea PasseriniSpringer LNCS · University of Trento · University of Modena and Reggio Emilia
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  4. 2021
    Self-Supervised Models are Continual LearnersEnrico Fini, Victor G. Turrisi da Costa, Xavier Alameda-Pineda … Julien MairalCVPR · University of Trento · Institut national de recherche en sciences et technologies du numérique · +1
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  5. 2022
    Continual Attentive Fusion for Incremental Learning in Semantic SegmentationGuanglei Yang, Enrico Fini, Dan Xu … Elisa RicciIEEE Trans. Multimedia · University of Trento · Harbin Institute of Technology · +5
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  6. 2022
    Uncertainty-aware Contrastive Distillation for Incremental Semantic SegmentationGuanglei Yang, Enrico Fini, Dan Xu … Elisa RicciTPAMI · Harbin Institute of Technology · University of Trento · +2
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  7. 2019
    Measuring Catastrophic Forgetting in Visual Question AnsweringClaudio Greco, Barbara Plank, Raquel Fernández, Raffaella BernardiSpringer LNCS · University of Trento · IT University of Copenhagen · +1
  8. 2020
    Few-Shot Unsupervised Continual Learning through Meta-ExamplesAlessia Bertugli, Stefano Vincenzi, Simone Calderara, Andrea PasseriniarXiv · University of Trento · University of Modena and Reggio Emilia
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  9. 2020
    Boosting Deep Open World Recognition by ClusteringDario Fontanel, Fabio Cermelli, Massimiliano Mancini … Barbara CaputoRA-L · Politecnico di Torino · Italian Institute of Technology · +4
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  10. 2020
    Modeling the Background for Incremental Learning in Semantic SegmentationFabio Cermelli, Massimiliano Mancini, Samuel Rota Bulò … Barbara CaputoCVPR · Politecnico di Torino · Italian Institute of Technology · +3
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  11. 2020
    Online Continual Learning under Extreme Memory ConstraintsEnrico Fini, Stéphane Lathuilière, Enver Sangineto … Elisa RicciSpringer LNCS · University of Trento · Télécom Paris · +2
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  12. 2019
    Incremental learning for the detection and classification of GAN-generated imagesFrancesco Marra, Cristiano Saltori, Giulia Boato, Luisa VerdolivaInternational Workshop on Information Forensics and Security · Federico II University Hospital · University of Trento
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  13. 2019
    Learning to Remember: A Synaptic Plasticity Driven Framework for Continual LearningOleksiy Ostapenko, Mihai Puscas, Tassilo Klein … Moin NabiCVPR · Humboldt-Universität zu Berlin · University of Trento · +1
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  14. 2019
    Psycholinguistics Meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question AnsweringClaudio Greco, Barbara Plank, Raquel Fernández, Raffaella BernardiOpen Research (University of Surrey) · University of Trento · IT University of Copenhagen · +1
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  15. 2018
    Adding New Tasks to a Single Network with Weight Trasformations using Binary MasksMassimiliano Mancini, Elisa Ricci, Barbara Caputo, Samuel Rota BulòSpringer LNCS · Fondazione Bruno Kessler · Sapienza University of Rome · +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. 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.