Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 4,574Sort Recent · Most cited
  1. 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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  2. 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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  3. 2025
    Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning PerspectiveLeyuan Wang, Liuyu Xiang, Yunlong Wang … Zhaofeng HeIEEE Trans. Multimedia · Beijing University of Posts and Telecommunications · Chinese Academy of Sciences · +2
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  4. 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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  5. 2025
    Unleashing the Power of Continual Learning on Non-Centralized Devices: A SurveyYichen Li, Haozhao Wang, Wenchao Xu … Ruixuan LiIEEE Communications Surveys & Tutorials · Huazhong University of Science and Technology · Hong Kong Polytechnic University · +5
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  6. 2024
    CP-Prompt: Composition-Based Cross-modal Prompting for Domain-Incremental Continual LearningYu Feng, Zhen Tian, Yifan Zhu … Meina SongACM International Conference on Multimedia · Beijing University of Posts and Telecommunications
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  7. 2024
    FSCIL-EACA: Few-Shot Class-Incremental Learning Network Based on Embedding Augmentation and Classifier Adaptation for Image ClassificationRuru Zhang, E Haihong, Meina SongChinese Journal of Electronics · Beijing University of Posts and Telecommunications
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  8. 2014
    An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural NetworksIan Goodfellow, Mehdi Mirza, Xiao Da … Yoshua BengioICLR · Département d'Informatique · Université de Montréal · +1
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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. 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, and only papers with a PDF we can point you at, so every title opens the paper itself. 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.