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.

10 papers of 4,574Sort Recent · Most cited
  1. 2026
    EvoHarnessBench: Can Your Agents Keep Pace with an Evolving Harness?Zixuan Ke, Vaidehi Patil, Haizhou Shi … Shafiq JotyarXiv
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  2. 2026PDF ↗
  3. 2026
    Guided Prompt Evolution for Vision-Language Models AdaptationEnming Zhang, Jiayang Li, Yanlong Wang … Yang LiarXiv
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  4. 2025
    Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic ScenariosLi Deng, Aming Wu, Yang Li … Yahong HanICCV · Tianjin University · Hefei University of Technology · +1
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  5. 2025
    Rethinking Continual Learning with Progressive Neural CollapseZheng Wang, Wenhua Yu, Yang Li, Sen LinICLR
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  6. 2025
    Exploiting Task Relationships in Continual Learning via Transferability-Aware Task EmbeddingsYanru Wu, Jianning Wang, Xiangyu Chen … Yang LiNeurIPS · Tsinghua University · Harbin Institute of Technology · +3
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  7. 2025
    Similarity-based context aware continual learning for spiking neural networksBing Han, Feifei Zhao, Yang Li … Yi ZengNeural Networks · Center for Excellence in Brain Science and Intelligence Technology · Beijing Academy of Artificial Intelligence · +3
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  8. 2024
    Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation DistillationJiyong Li, Dilshod Azizov, Yang Li, Shangsong LiangAAAI · Sun Yat-sen University · Mohamed bin Zayed University of Artificial Intelligence
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  9. 2024
    Learning a Low-Rank Feature Representation: Achieving Better Trade-Off Between Stability and Plasticity in Continual LearningZhenrong Liu, Yang Li, Yi Gong, Yik‐Chung WuICASSP · Southern University of Science and Technology · University of Hong Kong · +1
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  10. 2023PDF ↗
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.