Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

11 papers of 6,984Sort Recent · Most cited
  1. 2025
    Uni-IL: Unified Incremental Learning of Vision-Language Models via Mixture of Attribute-Guided ExpertsFanyu Meng, Yufeng Zhan, Jie Zhang … Yuanqing XiaACM International Conference on Multimedia in Asia · Beijing Institute of Technology · Hong Kong University of Science and Technology · +1
  2. 2025
    Theoretical Analysis of Mixture-of-Experts in Mobile Edge ComputingHongbo Li, Lingjie DuanIEEE Transactions · Singapore University of Technology and Design · Hong Kong University of Science and Technology
  3. 2025
    MDFAC: multi-dimensional feature adaptive calibration for generalized few-shot object detectionKailin Xie, Jinxiang Lai, Zijian She … Han ChenComplex & Intelligent Systems · Guangdong University of Technology · Hong Kong University of Science and Technology · +1
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  4. 2025
    TIPS: Two-level prompt selection for more stability-plasticity balance in continual learningZhikun Feng, Liang Peng, Kang Dang … Jionglong SuPattern Recognition · University of Electronic Science and Technology of China · Chengdu University of Information Technology · +3
  5. 2025
    Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail AnchorHao Yu, Xin Yang, Le Zhang … Qiang YangCVPR · Southwestern University of Finance and Economics · University of Electronic Science and Technology of China · +3
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  6. 2025
    Unleashing the Power of Continual Learning on Non-Centralized Devices: A SurveyYichen Li, Haozhao Wang, Wenchao Xu … Ruixuan LiIEEE Communications Surveys & Tutorials · Huazhong University of Science and Technology · Hong Kong Polytechnic University · +5
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  7. 2025
    Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-offSong Lai, Zhe Zhao, Fei Zhu … Gaofeng MengAAAI · City University of Hong Kong · City University of Hong Kong, Shenzhen Research Institute · +4
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  8. 2025
    Few-Shot Incremental Learning via Foreground Aggregation and Knowledge Transfer for Audio-Visual Semantic SegmentationJingqiao Xiu, Mengze Li, Zongxin Yang … Roger ZimmermannAAAI · National University of Singapore · Hong Kong University of Science and Technology · +4
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  9. 2025
    Prototype Conditioned Generative Replay for Continual Learning in NLPXi Chen, Min Zeng2025 Conference of the Nations of the Americas Chapter of… · Hong Kong University of Science and Technology
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  10. 2025
    RECALL: REpresentation-aligned Catastrophic-forgetting ALLeviation via Hierarchical Model MergingBowen Wang, Haiyuan Wan, Liwen Shi … Sheng ZhangEMNLP · University Town of Shenzhen · Tsinghua–Berkeley Shenzhen Institute · +6
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  11. 2025
    Task-wrapped Continual Learning in Task-Oriented Dialogue SystemsMin Zeng, Haiqin Yang, X. T. Chen, Yike GuoNAACL · Hong Kong University of Science and Technology
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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. It lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.