Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

15 papers of 6,984Sort Recent · Most cited
  1. 2025
    HMEN: A hybrid modular network with dynamic expansion for continual learningZiye Fang, Bo Wan, Shangqi Guo, Jian K. LiuKnowledge-Based Systems · Xidian University · Human Computer Interaction (Switzerland) · +2
  2. 2025
    REAL: Representation Enhanced Analytic Learning for Exemplar-free Class-incremental LearningRun He, Di Fang, Yizhu Chen … Huiping ZhuangKnowledge-Based Systems · South China University of Technology · Hong Kong Polytechnic University
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  3. 2025
    Multi-modality integrated class incremental learning networks for 3D object recognitionYufei Zhang, Dongyun Lin, Xiao Zhang … Huiping ZhuangKnowledge-Based Systems · Nanyang Technological University · Wuyi University · +4
  4. 2025
    STCKGE: Continual knowledge graph embedding based on spatial transformationXinyan Wang, Jinshuo Liu, Kaijian Xie … Jeff Z. PanKnowledge-Based Systems · Wuhan University of Technology · Wuhan University · +1
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  5. 2025
    MoTE: Mixture of task-specific experts for pre-trained model-based Class-incremental learningLinjie Li, Zhenyu Wu, Yang JiKnowledge-Based Systems · Beijing University of Posts and Telecommunications · Ministry of Education
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  6. 2025
    RACE: Robust adaptive and clustering elimination for noisy labels in continual learningYang Xiaolong, Guangda Lai, Dan Meng … Xin YangKnowledge-Based Systems · Southwestern University of Finance and Economics
  7. 2025
    Online task-free continual learning via discrepancy mechanismFei Ye, Adrian G. BorşKnowledge-Based Systems · University of Electronic Science and Technology of China · University of York
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  8. 2025
    Enhancing task incremental continual learning: integrating prompt-based feature selection with pre-trained vision-language modelLie Yang, Haohan Yang, Xiangkun He … Chen LvKnowledge-Based Systems · Nanyang Technological University
  9. 2025
    TSPT: Two-Step Prompt Tuning for class-incremental novel class discoveryJie An, Zhenbang Du, Herui Zhang, Dongrui WuKnowledge-Based Systems · Huazhong University of Science and Technology
  10. 2025
    Effective Generative Replay with Strong Memory for Continual LearningJing Yang, Xinyu Zhou, Yao He … Changfu ZhangKnowledge-Based Systems · Guizhou University · Shanghai Jiao Tong University · +2
  11. 2025
    Boundary-aware Prototype Augmentation and Dual-level Knowledge Distillation for Non-Exemplar Class-Incremental HashingQinghang Su, Dayan Wu, Bo LiKnowledge-Based Systems · Aerospace Information Research Institute · Institute of Information Engineering · +2
  12. 2025
    Class-wise federated unlearning: Harnessing active forgetting with teacher-student memory generationYuyuan Li, Jiaming Zhang, Yixiu Liu, Chaochao ChenKnowledge-Based Systems · Hangzhou Dianzi University · Zhejiang University of Science and Technology
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  13. 2025
    FeNeC: Enhancing Continual Learning via Feature Clustering with Neighbor- or Logit-Based ClassificationKamil Książek, Hubert Jastrzebski, Krzysztof Pniaczek … Jacek TaborKnowledge-Based Systems
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  14. 2025
    BEFM: A balanced and efficient fine-tuning model in class-incremental learningLize Liu, Jian Ji, Lei ZhaoKnowledge-Based Systems · Xidian University
  15. 2025
    Knowledge-guided prompt-based continual learning: Aligning task-prompts through contrastive hard negativesHengyang Lu, Lauren Lin, Chenyou Fan … Xiao‐Jun WuKnowledge-Based Systems · Jiangnan University · South China Normal 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 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. 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.