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.

6 papers of 8,653Sort Recent · Most cited
  1. 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
  2. 2025PDF ↗
  3. 2025
    Deconfound Semantic Shift and Incompleteness in Incremental Few-shot Semantic SegmentationYirui Wu, Yuhang Xia, Hao Li … Shaohua WanAAAI · Hohai University · Ministry of Water Resources of the People's Republic of China · +3
    PDF ↗
  4. 2023
    IOB: integrating optimization transfer and behavior transfer for multi-policy reuseSiyuan Li, Hao Li, Jin Zhang … Chongjie ZhangAutonomous Agents and Multi-Agent Systems · Harbin Institute of Technology · Northwestern Polytechnical University · +2
    PDF ↗
  5. 2022
    Task Adaptive Parameter Sharing for Multi-Task LearningMatthew Wallingford, Hao Li, Alessandro Achille … Stefano SoattoCVPR · University of Washington
    PDF ↗
  6. 2020
    A general fine-tune method for catastrophic forgettingTao Yang, Mingming Zhu, Hao Li, Yuan CaoMIPPR 2019: Automatic Target Recognition and Navigation · Wuhan Polytechnic 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. 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.