Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

17 papers of 8,653Sort Recent · Most cited
  1. 2026
    Self-adaptive Low-Rank Adaptation for Class-Incremental LearningYiming Song, Qiqi Duan, Lijun Sun … Yuhui ShiSpringer LNCS · Southern University of Science and Technology · Jiangxi University of Finance and Economics · +3
  2. 2026
    Flexible Knowledge Distillation for Class-Incremental Learning via Structural Knowledge TransferSeungmo Seo, Jongsu Youn, Jaehyung Bae, Jongwon ChoiSpringer LNCS · Chung-Ang University
  3. 2026
    Federated Class-Incremental Object DetectionMatthias Pijarowski, Matthias Rapp, Alexander Wolpert, Martin HeckmannSpringer LNCS · Hensoldt (Germany) · Hochschule Aalen
  4. 2026
    Kernel-Prototype Guided Background Adaptation for Class-Incremental Semantic SegmentationViet-Anh Tran Ngoc, Dinh-Nhat Loi, Thanh-Hai Dang, Quynh-Trang Pham ThiSpringer LNCS · Industrial University of Ho Chi Minh City · Ho Chi Minh City University of Industry and Trade
  5. 2026
    GRSNN: A Flexible Graph-Wired Spiking Neural Network for Neuromorphic Classification and Continual LearningXingyu Tao, Zhongjun Luo, Tomomi HashimotoSpringer LNCS · Guilin University of Electronic Technology · Saitama Institute of Technology
  6. 2026
    Multimodal Class-Incremental Learning Based on Wavelet Transform and Orthogonal ConstraintShile Yang, Yanjun YinSpringer LNCS · Inner Mongolia Normal University · Inner Mongolia Autonomous Region Meteorological Bureau · +1
  7. 2026
    The Effects of Task Similarity on Catastrophic Forgetting in Deep Residual NetworksChaolin Yang, Yonggang LuSpringer LNCS · Lanzhou University
  8. 2026
    Compositional Prompt Network for General Continual Learning in Decoupled Blurry ScenariosXiudong Chen, Yuehui ChenSpringer LNCS · University of Jinan
  9. 2026
  10. 2026
    Estimating Representation Drift for Prompt-Based Class-Incremental LearningYuting Hou, Rongyu Zhu, Junjie Liu, Kedian MuSpringer LNCS · Peking University
  11. 2026
    FbRA: Frequency-band Reconstruction and Adaptation for Few-Shot Class-Incremental LearningShile Yang, Yanjun YinSpringer LNCS · Inner Mongolia Normal University · Inner Mongolia Autonomous Region Meteorological Bureau · +1
  12. 2026
    Dynamic Elastic Weight Consolidation for Continual Learning in Spiking Neural NetworksJunxiu Liu, Puyang Li, Qiang Fu … Xue OuyangSpringer LNCS · Guangxi Normal University
  13. 2026
  14. 2026
    Hierarchical Bayesian Causal Modular Learning: A Two-Level Columnar Architecture for Continual LearningBen Goertzel, Charlie Derr, Yohannes TayeSpringer LNCS · Singularity University
  15. 2026
  16. 2026
    AdaHAT: Adaptive Hard Attention to the Task in Task-Incremental LearningPengxiang Wang, Hongbo Bo, Jun Hong … Kedian MuSpringer LNCS · Peking University · University of Bristol · +2
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  17. 2026
    cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time SeriesFederico Giannini, Giacomo Ziffer, Emanuele Della ValleSpringer LNCS · Politecnico di Milano
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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 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.