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
    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
    Elastic Multi-Gradient Descent for Parallel Continual LearningFan Lyu, Wei Feng, Yuepan Li … Liang WangTPAMI · Universitat Autònoma de Barcelona · Tianjin University · +2
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  3. 2026
    DECODE: Domain-Aware Continual Domain Expansion for Motion PredictionBoqi Li, Haojie Zhu, Henry LiuTPAMI · University of Michigan
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  4. 2026
    Dual-CBA: Improving Online Continual Learning via Dual Continual Bias Adaptors From a Bi-level Optimization PerspectiveHong Wang, Renzhen Wang, Yichen Wu … Deyu MengTPAMI · Xi'an Jiaotong University · Harvard University · +1
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  5. 2026
    Locally Linear Continual Learning for Time Series Based on VC-Theoretical Generalization BoundsYan V. G. Ferreira, Igor Barbosa Lima, Pedro H. G. Mapa S. … A. P. BragaTPAMI · Universidade Federal de Minas Gerais · University of Alberta
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  6. 2026
    Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel PerspectiveJingren Liu, Zhong Ji, Yunlong Yu … Xuelong LiTPAMI · Tianjin University · Zhejiang University · +3
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  7. 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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  8. 2026
    Lifelong Learning of Large Language Model Based Agents: A RoadmapJunhao Zheng, Chengming Shi, Xidi Cai … Qianli MaTPAMI · South China University of Technology · Mohamed bin Zayed University of Artificial Intelligence · +2
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  9. 2026PDF ↗
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.