Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

19 papers of 4,574Sort Recent · Most cited
  1. 2026
    G2LoRA: Gradient Orthogonal Low-Rank Adaptation Framework for Graph Continual Learning on Text-Attributed GraphsYuhan Wang, Yibo Ding, Yutong Ye … Jianxin LiKDD · Beihang University · Columbia University · +1
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  2. 2025
    Cross-Domain Attribute Alignment with CLIP: A Rehearsal-Free Approach for Class-Incremental Unsupervised Domain AdaptationKerun Mi, Guoliang Kang, Guangyu Li … Chen GongACM International Conference on Multimedia · Nanjing University of Science and Technology · Beihang University · +1
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  3. 2025PDF ↗
  4. 2025
    MKT: A Multi-Stage Knowledge Transfer Framework to Mitigate Catastrophic Forgetting in Multi-Domain Chinese Spelling CorrectionPeng Xing, Yinghui Li, Shirong Ma … Ying ShenEMNLP · Tsinghua–Berkeley Shenzhen Institute · Beihang University · +2
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  5. 2025
    Language-Inspired Relation Transfer for Few-Shot Class-Incremental LearningYifan Zhao, Jia Li, Zeyin Song, Yonghong TianTPAMI · Beihang University · Peking University
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  6. 2024
    MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality AssessmentKanglei Zhou, Liyuan Wang, Xingxing Zhang … Xiaohui LiangECCV · Durham University · Beihang University · +2
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  7. 2024
    Prompting Continual Person SearchPengcheng Zhang, Xiaohan Yu, Bai Xiao … Xin NingACM International Conference on Multimedia · Beihang University · Macquarie University · +2
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  8. 2024
    NC2D: Novel Class Discovery for Node ClassificationYue Hou, X. R. Chen, He Zhu … Ke XuCIKM · Beihang University · Communication University of China
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  9. 2024
    SCARF: Scalable Continual Learning Framework for Memory‐efficient Multiple Neural Radiance FieldsYuze Wang, Junyi Wang, Chen Wang … Yue QiComputer Graphics Forum · Beihang University · Shandong University of Science and Technology · +3
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  10. 2024PDF ↗
  11. 2024
    Hessian Aware Low-Rank Perturbation for Order-Robust Continual LearningJiaqi Li, Yuanhao Lai, Rui Wang … Fan ZhouTKDE · Western University · Vector Institute · +3
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  12. 2024PDF ↗
  13. 2023
    SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained ModelGengwei Zhang, Liyuan Wang, Guoliang Kang … Yunchao WeiICCV · University of Technology Sydney · Tsinghua University · +2
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  14. 2023
    AttriCLIP: A Non-Incremental Learner for Incremental Knowledge LearningRunqi Wang, Xiaoyue Duan, Guoliang Kang … Baochang ZhangCVPR · Huawei Technologies (Sweden) · Beihang University · +1
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  15. 2023PDF ↗
  16. 2023
    Unbiased and Efficient Self-Supervised Incremental Contrastive LearningCheng Ji, Jianxin Li, Hao Peng … Philip S. YuWSDM · Beihang University · Macquarie University · +1
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  17. 2021
    Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential ObservationsZike Yan, Yuxin Tian, Xuesong Shi … Hongbin ZhaICCV · King University · Peking University · +1
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  18. 2021
    Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNsYuwei Cao, Hao Peng, Jia Wu … Philip S. YuWWW · University of Illinois Chicago · Beihang University · +1
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  19. 2020
    Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesMengdi Xu, Wenhao Ding, Jiacheng Zhu … Ding ZhaoNeurIPS · Carnegie Mellon University · Tsinghua University · +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. 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, and only papers with a PDF we can point you at, so every title opens the paper itself. 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.