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.

9 papers of 8,653Sort Recent · Most cited
  1. 2024
    Continual Learning meets Multimodal Foundation Models: Fundamentals and AdvancesWenbin Li, Qi Fan, Rui Yan … Jiebo Luoon Continual Learning meets Multimodal Foundation Models:… · Nanjing University · Systems Engineering Society of China · +3
  2. 2024
    Incremental Image Generation with Diffusion Models by Label Embedding Initialization and FusionBing Li, Dongdong Ren, Hao Liu … Yang Gaoon Continual Learning meets Multimodal Foundation Models:… · Nanjing University · Tencent (China)
  3. 2024
    Class Incremental Learning via Semantic Information Mapping and Background Information CalibratingYan Xian, Hong Yu, Huaxiong Li, Guoyin WangIEEE TCSVT · Chongqing University of Posts and Telecommunications · Nanjing University
  4. 2024
    Class-Incremental Learning: A SurveyDa-Wei Zhou, Qiwei Wang, Zhihong Qi … Ziwei LiuTPAMI · Nanyang Technological University · Nanjing University
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  5. 2024
    InfLoRA: Interference-Free Low-Rank Adaptation for Continual LearningYan-Shuo Liang, Wu-Jun LiCVPR · Nanjing University
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  6. 2024
    Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental LearningDa-Wei Zhou, Hailong Sun, Han-Jia Ye, De-Chuan ZhanCVPR · Nanjing University
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  7. 2024
    Towards Backward-Compatible Continual Learning of Image CompressionZhihao Duan, Ming Lu, Justin Yang … Fengqing ZhuCVPR · Purdue University West Lafayette · Nanjing University
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  8. 2024
    Dynamic Replay Training for Class-Incremental LearningYan Yang, Dongdong Ren, Chenglei Peng … Yang GaoICASSP · Nanjing University · Nanjing University of Science and Technology
  9. 2024
    Efficient Bayesian Policy Reuse With a Scalable Observation Model in Deep Reinforcement LearningJinmei Liu, Zhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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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.