Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 5,456Sort Recent · Most cited
  1. 2025
    Infusing Fine-Grained Visual Knowledge to Vision-Language ModelsNikolaos-Antonios Ypsilantis, Kaifeng Chen, Andre B. Araujo, Ondřej ChumICCV · Czech Technical University in Prague · Google (United States) · +1
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  2. 2025
    Exemplar Masking for Multimodal Incremental LearningYi-Lun Lee, Chen-Yu Lee, Wei-Chen Chiu, Yi–Hsuan TsaiCVPR · National Yang Ming Chiao Tung University · Google (United States) · +1
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  3. 2025
    FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene UnderstandingThanh-Dat Truong, Utsav Prabhu, Bhiksha Raj … Khoa LuuCVPR · Google (United States) · Carnegie Mellon University · +2
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  4. 2025
    Continual Learning of Large Language Models: A Comprehensive SurveyHaizhou Shi, Zihao Xu, Hengyi Wang … Hao WangACM Computing Surveys · Rutgers, The State University of New Jersey · Google (United States) · +1
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  5. 2025
    LSEBMCL: A Latent Space Energy-Based Model for Continual LearningXiaodi Li, Dingcheng Li, Rujun Gao … Latifur KhanInternational Conference on Artificial Intelligence in In… · The University of Texas at Dallas · Google (United States) · +1
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  6. 2025
    Class-wise Balancing Data Replay for Federated Class-Incremental LearningZhuang Qi, Ying-Peng Tang, Lei Meng … Xiangxu MengNeurIPS · Shandong University · Nanyang Technological University · +1
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  7. 2025
    An Efficient Rehearsal Scheme for Catastrophic Forgetting Mitigation during Multi-stage Fine-tuningAndrew Bai, Chih-Kuan Yeh, Cho‐Jui Hsieh, A B TalyNAACL · University of California, Los Angeles · Google (United States)
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  8. 2025
    Learn and Ensemble Bridge Adapters for Multi-domain Task Incremental LearningZiqi Gu, Chunyan Xu, Wenxuan Fang … Zhen CuiNeurIPS · Nanjing University of Science and Technology · Google (United States) · +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. It lists only 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. 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.