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
    Recent Advances of Multimodal Continual Learning: A Comprehensive SurveyDianzhi Yu, Xinni Zhang, Yankai Chen … Irwin KingTNNLS · Chinese University of Hong Kong · Tsinghua University · +1
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  2. 2025
    Learning After Model DeploymentDerda Kaymak, Gyuhak Kim, Tomoya Kaichi … Bing LiuFrontiers · University of Illinois Chicago · Accenture (United States) · +1
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  3. 2025
    SPARC: Subspace-Aware Prompt Adaptation for Robust Continual Learning in LLMsDinithi Jayasuriya, Sina Tayebati, Davide Ettori … Amit Ranjan TrivediIJCNN · University of Illinois Chicago · Intel (United States)
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  4. 2023
    Dealing with Cross-Task Class Discrimination in Online Continual LearningYiduo Guo, Bing Liu, Dongyan ZhaoCVPR · Peking University · University of Illinois Chicago
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  5. 2023
    Rebalancing Batch Normalization for Exemplar-Based Class-Incremental LearningSungmin Cha, Sungjun Cho, Dasol Hwang … Taesup MoonCVPR · Seoul National University · University of Illinois Chicago
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  6. 2023
    AI Autonomy: Self-initiated Open-world Continual Learning and AdaptationBing Liu, Sahisnu Mazumder, Eric Robertson, Scott S. GrigsbyAI Magazine · University of Illinois Chicago · Intelligent Systems Research (United States) · +2
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  7. 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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  8. 2023
    Improving Gender Fairness of Pre-Trained Language Models without Catastrophic ForgettingZahra Fatemi, Xing Chen, Wenhao Liu, Caimming XiongACL · University of Illinois Chicago · University of Chicago · +1
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  9. 2022
    Continual Learning Based on OOD Detection and Task MaskingGyuhak Kim, Sepideh Esmaeilpour, Changnan Xiao, Bing LiuCVPR · University of Illinois Chicago
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  10. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
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  11. 2021
    Lifelong and Continual Learning Dialogue Systems: Learning during ConversationBing Liu, Sahisnu MazumderAAAI · University of Illinois Chicago
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  12. 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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  13. 2021
    Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification TasksZixuan Ke, Hu Xu, Bing LiuNAACL · University of Illinois Chicago · Meta (Israel)
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  14. 2021
    CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification TasksZixuan Ke, Bing Liu, Hu Xu, Lei ShuEMNLP · University of Illinois Chicago · Meta (Israel) · +1
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  15. 2021
    Continual Learning with Knowledge Transfer for Sentiment ClassificationZixuan Ke, Bing Liu, Hao Wang, Lei ShuSpringer LNCS · University of Illinois Chicago · Southwest Jiaotong University
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  16. 2020
    Lifelong Learning Dialogue Systems: Chatbots that Self-Learn On the JobBing Liu, Sahisnu MazumderarXiv · University of Illinois Chicago
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  17. 2019
    Forward and Backward Knowledge Transfer for Sentiment ClassificationHao Wang, Bing Liu, Shuai Wang … Yan YangMachine Learning · Southwest Jiaotong University · University of Illinois Chicago
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  18. 2017
    Lifelong Learning CRF for Supervised Aspect ExtractionLei Shu, Hu Xu, Bing LiuACL · University of Illinois Chicago
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  19. 2015
    Lifelong Machine Learning for Topic Modeling and BeyondZhiyuan ChenNAACL · University of Illinois Chicago
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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.