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.

9 papers of 4,574Sort Recent · Most cited
  1. 2026
    StructAlign: Structured Cross-Modal Alignment for Continual Text-to-Video RetrievalShaokun Wang, Weili Guan, Jizhou Han … Liqiang NieSIGIR · Harbin Institute of Technology · Shenzhen Institute of Information Technology · +2
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  2. 2026
    A Parametric Memory Head for Continual Generative RetrievalKidist Amde Mekonnen, Yubao Tang, Maarten de RijkeSIGIR · Amsterdam University of the Arts · University of Amsterdam
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  3. 2026
    Multi-Faceted Continual Knowledge Graph Embedding for Semantic-Aware Link PredictionJing Qi, Yuxiang Wang, Zhiyuan Yu … Tianxing WuSIGIR · Hangzhou Dianzi University · Xidian University · +1
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  4. 2025
    Continual Text-to-Video Retrieval with Frame Fusion and Task-Aware RoutingZecheng Zhao, Zhi Chen, Zi Huang … Tong ChenSIGIR · The University of Queensland · University of Southern Queensland
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  5. 2025
    Dynamic Time-aware Continual User Representation LearningS. K. Choi, Sein Kim, Hongseok Kang … Chanyoung ParkSIGIR · Korea Advanced Institute of Science and Technology
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  6. 2023
    Continual Learning on Dynamic Graphs via Parameter IsolationPeiyan Zhang, Yuchen Yan, Chaozhuo Li … Sunghun KimSIGIR · Hong Kong University of Science and Technology · Peking University · +3
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  7. 2023PDF ↗
  8. 2021
    TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph CompletionJiapeng Wu, Yishi Xu, Yingxue Zhang … Jackie Chi Kit CheungSIGIR · McGill University · Université de Montréal · +1
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  9. 2021
    Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment ClassificationBinzong Geng, Min Yang, Fajie Yuan … Ruifeng XuSIGIR · University of Science and Technology of China · Chinese Academy of Sciences · +5
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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.