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.

24 papers of 8,653Sort Recent · Most cited
  1. 2026
    CREAM: Continual Retrieval on Dynamic Streaming Corpora with Adaptive Soft MemoryHuijeong Son, Hyeongu Kang, Sunho Kim … Susik YoonKDD · Korea University · Yonsei University
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  2. 2026PDF ↗
  3. 2025
  4. 2025
    Does Prior Data Matter? Exploring Joint Training in the Context of Few-Shot Class-Incremental LearningShiwon Kim, Dongjun Hwang, Sungwon Woo, Rita SinghICCV · Yonsei University · Sogang University · +1
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  5. 2025
    Knowledge Distillation of Class Activation Maps from Two Teachers for Continual LearningMinkai Sheng, Hyung-Jun Moon, Sung‐Bae ChoSpringer LNCS · Yonsei University
  6. 2025
    Exploring Cross-Stage Adversarial Transferability in Class-Incremental Continual LearningJungwoo Kim, J. S. LeeIEEE International Workshop on Multimedia Signal Processi… · Yonsei University
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  7. 2025
    Continual Learning by Contrastive Learning of Regularized Classes in Multivariate Gaussian DistributionsHyung-Jun Moon, Sung‐Bae ChoInternational Journal of Neural Systems · Yonsei University
  8. 2024
    Federated Class Incremental Learning: A Pseudo Feature Based Approach Without ExemplarsMin Kyoon Yoo, Yu Rang ParkSpringer LNCS · Yonsei University
  9. 2024
    Differentiable Prototypes with Distributed Memory Network for Continual LearningMin-Seo Kwak, Hyung-Jun Moon, Sung‐Bae ChoSpringer LNCS · Yonsei University
  10. 2024
    Pre-trained Vision and Language Transformers are Few-Shot Incremental LearnersKeon-Hee Park, Kyungwoo Song, Gyeong-Moon ParkCVPR · Kyung Hee University · Yonsei University
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  11. 2024
    Learning Equi-Angular Representations for Online Continual LearningMinhyuk Seo, Hyunseo Koh, Wonje Jeung … Jonghyun ChoiCVPR · Yonsei University · Zhejiang Lab · +1
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  12. 2024
    Layer-wise Auto-Weighting for Non-Stationary Test-Time AdaptationJunyoung Park, Jin Kim, Hyeongjun Kwon … Kwanghoon SohnWACV · Yonsei University · Korea Institute of Science and Technology
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  13. 2024
  14. 2023
    Online Continual Learning on Hierarchical Label ExpansionByung Hyun Lee, Okchul Jung, Jonghyun Choi, Se Young ChunICCV · Seoul National University · Yonsei University
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  15. 2023
    Cost-effective On-device Continual Learning over Memory Hierarchy with MiroXinyue Ma, Suyeon Jeong, Minjia Zhang … Myeongjae JeonAnnual International Conference on Mobile Computing and N… · Ulsan National Institute of Science and Technology · Microsoft (United States) · +1
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  16. 2020
    A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World LearningMartin Mundt, Yongwon Hong, Iuliia Pliushch, Visvanathan RameshNeural Networks · Goethe University Frankfurt · Technische Universität Darmstadt · +1
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  17. 2023
    Task-aware network: Mitigation of task-aware and task-free performance gap in online continual learningYong Woo Hong, Hyeran Byun, Sungho ParkNeurocomputing · Yonsei University
  18. 2022
    Return of the normal distribution: Flexible deep continual learning with variational auto-encodersYongwon Hong, Martin Mundt, Sungho Park … Hyeran ByunNeural Networks · Yonsei University · Technische Universität Darmstadt · +1
  19. 2022
    CarM Hierarchical Episodic Memory for Continual LearningSoobee Lee, Minindu Weerakoon, Jonghyun Choi … Myeongjae JeonACM/IEEE Design Automation Conference · Ulsan National Institute of Science and Technology · Yonsei University · +1
  20. 2022
    Online Continual Learning on a Contaminated Data Stream with Blurry Task BoundariesJihwan Bang, Hyunseo Koh, Seulki Park … Jonghyun ChoiCVPR · NAVER Cloud (South Korea) · Naver (South Korea) · +2
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  21. 2019
    Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionMartin Mundt, Iuliia Pliushch, Sagnik Majumder … Visvanathan RameshJournal of Imaging · Goethe University Frankfurt · The University of Texas at Austin · +1
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  22. 2022
    Gradient Regularization with Multivariate Distribution of Previous Knowledge for Continual LearningTaeheon Kim, Hyung-Jun Moon, Sung‐Bae ChoSpringer LNCS · Yonsei University
  23. 2021
    Bayesian Optimization Based Efficient Layer Sharing for Incremental LearningBomi Kim, Taehyeon Kim, Yoonsik ChoeApplied Sciences · Yonsei University
  24. 2020
    A Novel Layer Sharing-based Incremental Learning via Bayesian OptimizationYoonsik Choe, Bomi Kim, Taehyeon KimApplied Sciences · Yonsei University
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.