Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

12 papers of 11,817Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2025PDF ↗
  3. 2025
    MLLM-CL: Continual Learning for Multimodal Large Language ModelsHongbo Zhao, Fei Zhu, Meng Wang … Zhaoxiang ZhangarXiv
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  4. 2025
    STCKGE: Continual knowledge graph embedding based on spatial transformationXinyan Wang, Jinshuo Liu, Kaijian Xie … Jeff Z. PanKnowledge-Based Systems
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  5. 2025
    Knowledge Swapping via Learning and UnlearningMingyu Xing, Lechao Cheng, Shen-Geng Tang … Meng WangICML
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  6. 2025
    Navigating Semantic Drift in Task-Agnostic Class-Incremental LearningFangwen Wu, Lechao Cheng, Shengeng Tang … Meng WangICML
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  7. 2024PDF ↗
  8. 2024
    Densely Distilling Cumulative Knowledge for Continual LearningZenglin Shi, Pei Liu, Tong Su … Meng WangarXiv
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  9. 2022
    Continual Referring Expression Comprehension via Dual Modular MemorizationHeng Tao Shen, Cheng Chen, Peng Wang … Jingkuan SongTIP · University of Electronic Science and Technology of China · Peng Cheng Laboratory · +2
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  10. 2022
  11. 2021
    A dynamic routing CapsNet based on increment prototype clustering for overcoming catastrophic forgettingMeng Wang, Zhengbing Guo, Huafeng LiIET Computer Vision · Kunming University of Science and Technology · Kunming University · +1
  12. 2021
    Multi-task continuous learning modelZhengbing Guo, Meng WangJournal of Physics, Conference Series
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.