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.

13 papers of 8,653Sort Recent · Most cited
  1. 2026
    Reinforced Interactive Continual Learning via Real-time Noisy Human FeedbackYutao Yang, Jie Zhou, Junsong Li … Liang HeExpert Systems with Applications · East China Normal University · Shanghai Xuhui Central Hospital
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  2. 2026PDF ↗
  3. 2026PDF ↗
  4. 2026
    AutoSkill: Experience-Driven Lifelong Learning via Skill Self-EvolutionYutao Yang, Junsong Li, Qianjun Pan … Liang HearXiv
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  5. 2026
    Adaptive Momentum Mixture-of-Experts for Continual Visual Question AnsweringTianyu Huai, Jie Zhou, Qin Chen … Liang HeIEEE TCSVT · East China Normal University · Shanghai Open University · +2
  6. 2025PDF ↗
  7. 2025PDF ↗
  8. 2025PDF ↗
  9. 2025
    CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question AnsweringTianyu Huai, Jie Zhou, Xingjiao Wu … Liang HeCVPR · East China Normal University · Shanghai Open University · +1
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  10. 2025PDF ↗
  11. 2024
    Recent Advances of Foundation Language Models-based Continual Learning: A SurveyYutao Yang, Jie Zhou, Xuanwen Ding … Liang HeACM Computing Surveys · East China Normal University
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  12. 2024
    PI-Fed: Continual Federated Learning With Parameter-Level Importance AggregationLang Yu, Lina Ge, Guanghui Wang … Liang HeIEEE Internet of Things Journal
  13. 2024PDF ↗
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.