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.

5 papers of 8,653Sort Recent · Most cited
  1. 2026
    Leveraging multi-modal and historical knowledge graphs for continual robot navigationLin Zhang, Longyue Qian, Ruitong Li … Wei ZhangVisual Intelligence · Ministry of Education of the People's Republic of China · Shandong University · +2
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  2. 2026
    Semantic-aware replay and key knowledge fusion for 3D continual learningLongyue Qian, Lin Zhang, Jing Wang … Mingxin ZhangBiomimetic Intelligence and Robotics · Shandong University · Ministry of Education · +2
  3. 2025
    A continual imitation learning benchmark for mobile robot navigation in sequential environmentsRui Li, Y. H. Xie, Lin Zhang … Wei ZhangRobotic Intelligence and Automation · Shandong University · University of Jinan · +1
  4. 2024
    Learning to Navigate Sequential Environments: A Continual Learning Benchmark for Multi-modal NavigationY. H. Xie, Yuenan Zhao, Qian Zhang … Wei ZhangIEEE International Conference on Robotics and Biomimetics… · Shandong University
  5. 2024
    Parameter-level Mask-based Adapter for 3D Continual Learning with Vision-Language ModelLongyue Qian, Mingxin Zhang, Qian Zhang … Wei ZhangIEEE International Conference on Robotics and Biomimetics… · Shandong 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. 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.