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.

11 papers of 11,817Sort Recent · Most cited
  1. 2026
    MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic MemoryShengtao Zhang, Jia-Qian Wang, Ruiwen Zhou … Muning WenarXiv
    PDF ↗
  2. 2025
    MemOS: A Memory OS for AI SystemZhiyu Li, Shichao Song, Chenyang Xi … Feiyu XiongarXiv
    PDF ↗
  3. 2024PDF ↗
  4. 2023PDF ↗
  5. 2023
    Lifelong Learning With Cycle Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiTNNLS
  6. 2021
    Overcome Anterograde Forgetting with Cycled Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiarXiv
    PDF ↗
  7. 2021
    Reviewing continual learning from the perspective of human-level intelligenceYifan Chang, Wenbo Li, Jian Peng … Haifeng LiarXiv
    PDF ↗
  8. 2021
    Learning by Active Forgetting for Neural NetworksJian Peng, Xian Sun, Min Deng … Haifeng LiarXiv · Central South University
    PDF ↗
  9. 2019
    Overcoming Long-Term Catastrophic Forgetting Through Adversarial Neural Pruning and Synaptic ConsolidationJian Peng, Bo Tang, Hao Jiang … Haifeng LiTNNLS · Central South University · Mississippi State University · +3
    PDF ↗
  10. 2020
    An Incremental Learning Based Edge Caching System: From Modeling to EvaluationGuangping Xu, Bo Tang, Liming Yuan … Chi Wan SungIEEE Access · Tianjin University of Technology · City University of Hong Kong
  11. 2018
    MILE: A minimally interactive learning framework for visual data analysisBo Tang, Haibo HeJournal of Media Literacy Education · Mississippi State University · University of Rhode Island
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.