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.

21 papers of 8,653Sort Recent · Most cited
  1. 2025
    CAST-GNN: Continual Adaptive Learning for Custom Spatio-Temporal Knowledge Graphs via Graph Neural NetworksGözde Ayşe Tataroğlu Özbulak, Yash Raj Shrestha, Jean-Paul CalbimonteICDM · University of Lausanne · HES-SO University of Applied Sciences and Arts Western Switzerland
  2. 2025
    GEM-Style Constraints for PEFT with Dual Gradient Projection in LoRABrian Tekmen, Jason Yin, Qianqian TongICDM · University of North Carolina at Greensboro · North Carolina State University
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  3. 2025
    LifelongSkill: Toward Modality-Varying Lifelong Learning with Latent Knowledge HypergraphJiayi Chen, Kishlay Jha, Aidong ZhangICDM · University of Virginia · University of Iowa
  4. 2025
    Mitigating Catastrophic Forgetting Using Improved Clustering-Based Episodic MemoryOwen Beabout, Abigail Dodd, Titus Murphy, Enyue LuICDM · Salisbury University · University of Virginia · +1
  5. 2023
    CaT: Balanced Continual Graph Learning with Graph CondensationYilun Liu, Ruihong Qiu, Zi HuangICDM · The University of Queensland
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  6. 2023
    Continual Semantic Segmentation via Scalable Contrastive Clustering and Background DiversityQi Yang, Xing Nie, Linsu Shi … Shiming XiangICDM · Chinese Academy of Sciences · Institute of Automation · +1
  7. 2023
    Mixup-Inspired Video Class-Incremental LearningJinqiang Long, Yizhao Gao, Zhiwu LuICDM · Renmin University of China
  8. 2022
    Sparsified Subgraph Memory for Continual Graph Representation LearningXikun Zhang, Dongjin Song, Dacheng TaoICDM · The University of Sydney · University of Connecticut
  9. 2022
    A study of the Dream Net model robustness across continual learning scenariosMarion Mainsant, Martial Mermillod, Christelle Godin, Marina ReybozICDM · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · CEA Grenoble · +3
  10. 2022PDF ↗
  11. 2021
    Continual Learning for Multivariate Time Series Tasks with Variable Input DimensionsVibhor Gupta, Jyoti Narwariya, Pankaj Malhotra … Gautam ShroffICDM
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  12. 2021
    Few-Shot Class-Incremental Learning with Meta-Learned Class StructuresGuangtao Zheng, Aidong ZhangICDM · University of Virginia
  13. 2021
    Evaluating and Explaining Generative Adversarial Networks for Continual Learning under Concept DriftFilip Guzy, Michał Woźniak, Bartosz KrawczykICDM · University of Science and Technology · AGH University of Krakow · +1
  14. 2021
    SGDOL: Self-evolving Generative and Discriminative Online Learning for Data Stream ClassificationDeeksha Aggarwal, J. Senthilnath, Uttam Kumar … Xiaoli LiICDM · International Institute of Information Technology Bangalore · Agency for Science, Technology and Research · +2
  15. 2020
    Learn-Prune-Share for Lifelong LearningZifeng Wang, Tong Jian, Kaushik Chowdhury … Stratis IoannidisICDM · Northeastern University
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  16. 2019
    MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream ClassificationMonidipa Das, Mahardhika Pratama, Septiviana Savitri, Jie ZhangICDM · Nanyang Technological University
  17. 2019
  18. 2019
    Primitives Generation Policy Learning without Catastrophic Forgetting for Robotic ManipulationFangzhou Xiong, Zhiyong Liu, Kaizhu Huang … Amir HussainICDM · Shandong Institute of Automation · University of Chinese Academy of Sciences · +4
  19. 2018
    Imbalanced Augmented Class Learning with Unlabeled Data by Label Confidence PropagationSiyu Ding, Xuying Liu, Min-Ling ZhangICDM · Southeast University
  20. 2018
    Clustered Lifelong Learning Via Representative Task SelectionGan Sun, Yang Cong, Yu Kong, Xiaowei XuICDM · University of Chinese Academy of Sciences · Shenyang Institute of Automation · +3
  21. 2017
    New Class Adaptation Via Instance Generation in One-Pass Class Incremental LearningYue Zhu, Kai Ming Ting, Zhi‐Hua ZhouICDM · Nanjing University · Federation 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. 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.