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.

11 papers of 8,653Sort Recent · Most cited
  1. 2024
    Memory-Enhanced Confidence Calibration for Class-Incremental Unsupervised Domain AdaptationJiaping Yu, Muli Yang, Aming Wu, Cheng DengIEEE Trans. Multimedia · Xidian University · Agency for Science, Technology and Research · +1
  2. 2024
    A Class Incremental Learning Method Based on Class Rebalancing and Old Knowledge TransferJialun Song, Lan Du, Jian ChenIEEE International Conference on Signal, Information and… · Xidian University
  3. 2024
  4. 2024
    Efficient Statistical Sampling Adaptation for Exemplar-Free Class Incremental LearningDe Cheng, Yuxin Zhao, Nannan Wang … Xinbo GaoIEEE TCSVT · Xidian University · Northwestern Polytechnical University · +1
  5. 2024
    Long-Tail Class Incremental Learning via Independent SUb-Prototype ConstructionXi Wang, Yang Xu, Jie Yin … Cheng DengCVPR · Xidian University
  6. 2024
  7. 2024
    Progressive Adapting and Pruning: Domain-Incremental Learning for Saliency PredictionKaihui Yang, Junwei Han, Guangyu Guo … Dingwen ZhangACM Transactions · Nanchang University · Northwestern Polytechnical University · +4
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  8. 2024
    Rebalancing network with knowledge stability for class incremental learningJialun Song, Jian Chen, Lan DuPattern Recognition · Xidian University
  9. 2024
    Continual learning for cross-modal image-text retrieval based on domain-selective attentionRui Yang, Shuang Wang, Yu Gu … Licheng JiaoPattern Recognition · Xidian University
  10. 2024
    Class-Incremental Unsupervised Domain Adaptation via Pseudo-Label DistillationKun Wei, Xu Yang, Zhe Xu, Cheng DengTIP · Xidian University
  11. 2024
    Incremental Embedding Learning With Disentangled Representation TranslationKun Wei, Da Chen, Yuhong Li … Dacheng TaoTNNLS · Xidian University · Alibaba Group (China) · +1
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.