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.

12 papers of 8,653Sort Recent · Most cited
  1. 2026
    TriP: A triple-prompt framework aligning pre-training and class-incremental objectives in continual graph learning.Can-Ming Cui, Hui-yu Zhou, Pei-Yuan Lai, Chang‐Dong WangNeural Networks · Sun Yat-sen University · Guangxi Zhuang Autonomous Region Health and Family Planning · +1
  2. 2026
    ASMem: Anchor sparse memory for multi-domain knowledge editing of large language modelsGuanyu Zheng, Zhenyu Wang, Yang Zhao … Chengqing ZongNeural Networks · South China University of Technology · Shandong Institute of Automation · +3
  3. 2026
    Randomized neural network with adaptive forward regularization for online task-free class incremental learningJunda Wang, Minghui Hu, Ning Li … Ponnuthurai Nagaratnam SuganthanNeural Networks · Shanghai Jiao Tong University · Nanyang Technological University · +1
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  4. 2026
    Learning forward-compatible and domain-invariant representations for cross-domain few-shot class-incremental learningWeidong Shi, Xudong Yan, Jiazheng Yuan … Songhe FengNeural Networks · Beijing Jiaotong University · Beijing Normal University · +3
  5. 2026
    Towards continual low-light image enhancement through causal inferenceFan Ji, Hao Li, Jiangmeng Li … Fanjiang XuNeural Networks · Institute of Software · Aerospace Information Research Institute · +1
  6. 2026
    A continual learning framework with long-term and multiple short-term memory networksShangge Liu, Lei Wang, Rui Yan … Yang GaoNeural Networks · Nanjing Tech University · University of Wollongong · +2
  7. 2026
    Dual-modality adaptation in vision-language models for continual learningJiahao Zeng, Wentao Zhang, Kanghao Chen … Ruixuan WangNeural Networks · Sun Yat-sen University · GCI Science & Technology (China) · +1
  8. 2026
    Dual prototypes for adaptive pre-trained model in class-incremental learningZhiming Xu, Zhiming Xu, Suorong Yang … Jian ZhaoNeural Networks · Nanjing University · Nanjing University of Science and Technology
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  9. 2026
    Continual learning: A systematic literature reviewQinwen Yang, Liyuan Wang, Joerg Wicker, Gillian DobbieNeural Networks · University of Auckland · Tsinghua University · +1
  10. 2026
    Rethinking softmax in incremental learningZheng Zhai, Jiali Zhang, Haiyu Wang … Qiang SunNeural Networks · Beijing Normal-Hong Kong Baptist University · Beijing Normal University · +4
  11. 2026
    C3GAN: A brain-inspired memory consolidation for class-incremental learningLin Xiong, Tao Wang, Fuqing Zhang … Hailing XiongNeural Networks · Southwest University · Chongqing Jiaotong University · +2
  12. 2026
    Generative Binary Memory: Pseudo-Replay Class-Incremental Learning on Binarized EmbeddingsYanis Basso-Bert, Anca Molnos, Romain Lemaire … Antoine DupretNeural Networks
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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. 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.