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.

13 papers of 4,574Sort Recent · Most cited
  1. 2026
    FOCUS: Frequency-Optimized Conditioning of diffUSion models for mitigating catastrophic forgetting during test-time adaptationGabriel Tjio, Jie Zhang, Xulei Yang … Qing GuoMachine Vision and Applications · Agency for Science, Technology and Research · Nanyang Technological University · +4
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  2. 2025
    Caption, Create, Continue: Continual Learning with Pre-trained Generative Vision-Language ModelsIndu Solomon, Aye Phyu Phyu Aung, Uttam Kumar, J. SenthilnathCIKM · International Institute of Information Technology Bangalore · Agency for Science, Technology and Research · +1
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  3. 2025
    PROL: Rehearsal Free Continual Learning in Streaming Data via Prompt Online LearningM. Anwar Ma’sum, Mahardhika Pratama, Savitha Ramasamy … Ryszard KowalczykICCV · University of South Australia · Institute for Infocomm Research
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  4. 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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  5. 2024
    PIP: Prototypes-Injected Prompt for Federated Class Incremental LearningM. Anwar Ma’sum, Mahardhika Pratama, Savitha Ramasamy … Ryszard KowalczykCIKM · University of South Australia · Institute for Infocomm Research
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  6. 2024
    Developmental Predictive Coding Model for Early Infancy Mono and Bilingual Vocal Continual LearningXiaodan Chen, Alexandre Pitti, Mathias Quoy, Nancy F. ChenSpringer LNCS · Agency for Science, Technology and Research · Centre National de la Recherche Scientifique · +7
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  7. 2021
    Tuned Compositional Feature Replays for Efficient Stream LearningMorgan B. Talbot, Rushikesh Zawar, Rohil Badkundri … Gabriel KreimanTNNLS · Boston Children's Hospital · Harvard–MIT Division of Health Sciences and Technology · +6
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  8. 2021
    Continual Learning: Fast and SlowQuang Pham, Chenghao Liu, Steven C. H. HoiTPAMI · Institute for Infocomm Research · Singapore Management University
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  9. 2023
    Multi-Modal Continual Test-Time Adaptation for 3D Semantic SegmentationHaozhi Cao, Yuecong Xu, Jianfei Yang … Lihua XieICCV · Nanyang Technological University · Agency for Science, Technology and Research · +1
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  10. 2022
    Online Lifelong Generalized Zero-Shot LearningChandan Gautam, Sethupathy Parameswaran, Ashish Mishra, Suresh SundaramNeural Networks · Agency for Science, Technology and Research · Institute for Infocomm Research · +2
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  11. 2022
    Progressive Continual Learning for Spoken Keyword SpottingYizheng Huang, Nana Hou, Nancy F. ChenICASSP · Agency for Science, Technology and Research · Institute for Infocomm Research · +1
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  12. 2022
    Preventing Catastrophic Forgetting and Distribution Mismatch in Knowledge Distillation via Synthetic DataKuluhan Binici, Nam Trung Pham, Tulika Mitra, Karianto LemanWACV · Agency for Science, Technology and Research · National University of Singapore · +1
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  13. 2022
    Knowledge Capture and Replay for Continual LearningSaisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Haytham M. Fayek … ArulMurugan AmbikapathiWACV · Agency for Science, Technology and Research · Institute for Infocomm Research · +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.