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.

9 papers of 11,817Sort Recent · Most cited
  1. 2024
    Towards Optical Transport Network: From the Management Perspective of Digital Twin ModelYuting Ma, Ji-Fan Yang, Yu Zhou … Shan-Guo HuangGlobal Communications Conference
  2. 2024
    Towards Rehearsal-Free Multilingual ASR: A LoRA-based Case Study on WhisperTianyi Xu, Kaixun Huang, Pengcheng Guo … Lei XieInterspeech
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  3. 2024
    MixER: Mixup-Based Experience Replay for Online Class-Incremental LearningW. Lim, Yu Zhou, Dae-Won Kim, Jaesung LeeIEEE Access
  4. 2022PDF ↗
  5. 2021
    Multi-View Correlation Distillation for Incremental Object DetectionDongbao Yang, Yu Zhou, Aoting Zhang … Qixiang YePattern Recognition · Chinese Academy of Sciences · Institute of Information Engineering · +1
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  6. 2022
    RD-IOD: Two-Level Residual-Distillation-Based Triple-Network for Incremental Object DetectionDongbao Yang, Yu Zhou, Wei Shi … Weiping WangACM Transactions · University of Chinese Academy of Sciences · Chinese Academy of Sciences · +1
  7. 2020
    Continual Learning in Task-Oriented Dialogue SystemsAndrea Madotto, Zhaojiang Lin, Zhenpeng Zhou … Zhiguang WangEMNLP · Hong Kong University of Science and Technology · Meta (Israel) · +1
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  8. 2020PDF ↗
  9. 2019
    On the area scalability of valence-change memristors for neuromorphic computingD. S. Ang, Yu Zhou, K. S. Yew, Dan BercoApplied Physics Letters · Nanyang Technological 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.