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.

7 papers of 6,984Sort Recent · Most cited
  1. 2026
    EA: Elastic multi-level anchoring-based generative approach for federated class-incremental learningWanxin Wu, Gang Li, Lixin Liu … Jianfeng ZhaoExpert Systems with Applications · Inner Mongolia University of Science and Technology · Wuhan University of Technology · +1
  2. 2026
    Parameter-Efficient Continuous Adaptation of Large Models in Hierarchical Federated NetworksWanrou Du, Yixuan Li, Xiaoqi Qin … Ping ZhangIEEE International Conference on Communications Workshops… · Beijing University of Posts and Telecommunications · State Key Laboratory of Networking and Switching Technology · +3
  3. 2026
    LDEPrompt: Layer-importance guided Dual Expandable Prompt Pool for Pre-trained Model-based Class-Incremental LearningLinjie Li, Zhenyu Wu, Huiyu Xiao, Jie YangICASSP · Beijing University of Posts and Telecommunications
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  4. 2026
    Self-Evolving LLMs via Continual Instruction TuningJiazheng Kang, Le Huang, Cheng Hou … Ting BaiACM Web Conference 2026 · Beijing University of Posts and Telecommunications
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  5. 2026
    LUNCH: adaptive balancing of continual learning via hyperparameter uncertaintyQingyi Pan, Liyuan Wang, Jingyi Zhang, Jun ZhuInformation Sciences · Tsinghua University · Beijing University of Posts and Telecommunications
  6. 2026
    Emotion-augmented continual learning for empathic robot behaviorYuxuan Zhao, Tongwei Zhang, Siqi Liu … Wei WuExpert Systems with Applications · Chinese Academy of Sciences · Shandong Institute of Automation · +3
  7. 2026
    Symmetric Image-Text Tuning With Entropy-Guided Fusion for Online Continual Learning in Non-Stationary Visual StreamsLeyuan Wang, Liuyu Xiang, Yujie Wei … Zhaofeng HeTIP · Beijing University of Posts and Telecommunications · Shandong Institute of Automation · +1
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.