Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

22 papers of 4,574Sort Recent · Most cited
  1. 2026
    GRASP: Gradient-Aligned Sequential Parameter Transfer for Memory-Efficient Multi-Source LearningMary Isabelle Wisell, Nicholas Jacobs, Aayush Manandhar, Salimeh Yasaei SekehICPR
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  2. 2026
    Tunable MAGMAX: Preference-Aware Model Merging for Continual LearningKei Hiroshima, Kento Uchida, Shinichi ShirakawaICPR
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  3. 2026
    STAER: Temporal Aligned Rehearsal for Continual Spiking Neural NetworkMatteo Gianferrari, Omayma Moussadek, Riccardo Salami … Simone CalderaraICPR
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  4. 2024
    FedRewind: Rewinding Continual Model Exchange for Decentralized Federated LearningLuca Palazzo, Matteo Pennisi, Federica Proietto Salanitri … Concetto SpampinatoICPR
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  5. 2024PDF ↗
  6. 2024PDF ↗
  7. 2024
    Mask and Compress: Efficient Skeleton-based Action Recognition in Continual LearningMatteo Mosconi, Andriy Sorokin, Aniello Panariello … Rita CucchiaraICPR
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  8. 2024
    Alleviating Catastrophic Forgetting in Facial Expression Recognition with Emotion-Centered ModelsR. IsraelA.Laurensi, A. de Souza Britto, J. P. Barddal, A. KoerichICPR
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  9. 2024PDF ↗
  10. 2024
    Face to Cartoon Incremental Super-Resolution using Knowledge DistillationTrinetra Devkatte, Shiv Ram Dubey, Satish Kumar Singh, Abdenour HadidICPR
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  11. 2023PDF ↗
  12. 2023PDF ↗
  13. 2022
    Effects of Auxiliary Knowledge on Continual LearningGiovanni Bellitto, Matteo Pennisi, Simone Palazzo … Simone CalderaraICPR · University of Catania · University of Modena and Reggio Emilia
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  14. 2022
    Rethinking Task-Incremental Learning BaselinesMd. Sazzad Hossain, Pritom Saha, Townim Faisal Chowdhury … Nabeel MohammedICPR · Grameenphone (Bangladesh) · North South University
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  15. 2022
    KRNet: Towards Efficient Knowledge ReplayYingying Zhang, Qiaoyong Zhong, Di Xie, Shiliang PuICPR
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  16. 2021
    Rethinking Experience Replay: a Bag of Tricks for Continual LearningPietro Buzzega, Matteo Boschini, Angelo Porrello, Simone CalderaraICPR · University of Modena and Reggio Emilia
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  17. 2021
    Class-incremental Learning with Pre-allocated Fixed ClassifiersFederico Pernici, Matteo Bruni, Claudio Baecchi … Alberto Del BimboICPR · Florence (Netherlands) · University of Florence
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  18. 2021
    Sequential Domain Adaptation through Elastic Weight Consolidation for Sentiment AnalysisAvinash Madasu, Anvesh Rao VijjiniICPR · Samsung (United States) · Samsung (India)
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  19. 2021
    ARCADe: A Rapid Continual Anomaly DetectorAhmed Frikha, Denis Krompaß, Volker TrespICPR · Siemens (Germany)
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  20. 2021
    Incrementally Zero-Shot Detection by an Extreme Value AnalyzerSixiao Zheng, Yanwei Fu, Yanxi HouICPR · Fudan University
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  21. 2021
    Pseudo Rehearsal using non photo-realistic imagesBhasker Sri Harsha Suri, Kalidas YeturuICPR · Indian Institute of Technology Tirupati
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  22. 2018
    Rotate your Networks: Better Weight Consolidation and Less Catastrophic ForgettingXialei Liu, Marc Masana, Luis Herranz … Andrew D. BagdanovICPR · Computer Vision Center · University of Florence
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times, and only papers with a PDF we can point you at, so every title opens the paper itself. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.