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.

13 papers of 5,456Sort Recent · Most cited
  1. 2026
    Crafting Your Evolving Dreams: Concept-Incremental Versatile CustomizationJiahua Dong, Wenqi Liang, Hongliu Li … Fahad Shahbaz KhanTPAMI · Mohamed bin Zayed University of Artificial Intelligence · University of Trento · +5
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  2. 2026
    Randomized neural network with adaptive forward regularization for online task-free class incremental learningJunda Wang, Minghui Hu, Ning Li … Ponnuthurai Nagaratnam SuganthanNeural Networks · Shanghai Jiao Tong University · Nanyang Technological University · +1
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  3. 2026
    Beyond catastrophic forgetting: A continual learning-driven multi-modal fusion model for saliency prediction in dynamic scenesNana Zhang, Yi-Xiang Wang, Dandan Zhu … Guangtao ZhaiExpert Systems with Applications · Donghua University · Tongji University · +1
  4. 2026
    UIKG: New Uncertain-Dynamic Incremental Knowledge GraphsZhangcong Xu, Gumin Jin, Guangyao Wang, Li JChinese Control and Decision Conference (CCDC) · Shanghai Jiao Tong University · Shenyang Aerospace University
  5. 2026
    From Cold-Start to Stabilization: A Dual-Prototype Framework for Online Any-Shot Continual LearningChengyan Liu, Linglan Zhao, Juping Gu … Fan LyuICASSP · Suzhou University of Science and Technology · Shanghai Jiao Tong University
  6. 2026
    Vision-Language Efficient Tuning for Mitigating Catastrophic Forgetting in Multi-Modal LearningYaoming Wang, Yuchen Liu, Wenrui Dai … Hongkai XiongIJCV · Shanghai Jiao Tong University · Huawei Technologies (China)
  7. 2026
    Learning From Each Other: Generalized Federated Incremental Semantic SegmentationJiahua Dong, Wenqi Liang, Yang Cong … Luc Van GoolTPAMI · Mohamed bin Zayed University of Artificial Intelligence · Shenyang Institute of Automation · +5
  8. 2026
    Incremental Online Learning of Randomized Neural Network With Forward RegularizationJunda Wang, Minghui Hu, Ning Li … Ponnuthurai Nagaratnam SuganthanTPAMI · Shanghai Jiao Tong University · Nanyang Technological University · +1
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  9. 2026
    Generalizable and Adaptive Continual Learning Framework for AI-Generated Image DetectionHanyi Wang, Jun Lan, Yaoyu Kang … Shilin WangIEEE Trans. Multimedia · Shanghai Jiao Tong University
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  10. 2026
    Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment TaxZeli Su, Ziyin Zhang, Zhou Liu … Wentao ZhangACL · Minzu University of China · Shanghai Jiao Tong University · +4
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  11. 2026
    SLoRA: Balancing Plasticity and Forgetting in Large Language Models for Continual LearningLina Yang, Yusheng Liao, Yanfeng Wang, Yu Guang WangACL · Shanghai Jiao Tong University
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  12. 2026
    Developing Evolving Adaptability in Biological Intelligence: A Novel Biologically-Inspired Continual Learning Model for Video Saliency PredictionDandan Zhu, Kaiwei Zhang, Kun Zhu … Xiaokang YangTPAMI · East China Normal University · Shanghai Artificial Intelligence Laboratory · +3
  13. 2026
    A Theoretical Perspective on Streaming Noisy Data With Distribution ShiftWenshui Luo, Shuo Chen, Tao Zhou, Chen GongTPAMI · Shanghai Jiao Tong University · Nanjing University of Science and Technology
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.