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.

8 papers of 4,574Sort Recent · Most cited
  1. 2024
    ECIL-MU: Embedding Based Class Incremental Learning and Machine UnlearningZhiwei Zuo, Zhuo Tang, Bin Wang … Anwitaman DattaICASSP · Hunan University · Nanyang Technological University
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  2. 2024
    Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training StrategyJunsu Kim, Sumin Hong, Chanwoo Kim … Seungryul BaekICASSP · Ulsan National Institute of Science and Technology · Seoul National University of Science and Technology · +3
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  3. 2024
    INCPrompt: Task-Aware Incremental Prompting for Rehearsal-Free Class-Incremental LearningZhiyuan Wang, Xiaoyang Qu, Jing Xiao … Jianzong WangICASSP · Tsinghua–Berkeley Shenzhen Institute · Shenzhen Technology University · +3
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  4. 2024PDF ↗
  5. 2024
    P2DT: Mitigating Forgetting in Task-Incremental Learning with Progressive Prompt Decision TransformerZhiyuan Wang, Xiaoyang Qu, Jing Xiao … Jianzong WangICASSP · Tsinghua–Berkeley Shenzhen Institute · Shenzhen Technology University · +3
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  6. 2024
    Generalizable Two-Branch Framework for Image Class-Incremental LearningChao Wu, Xiaobin Chang, Ruixuan WangICASSP · Sun Yat-sen University
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  7. 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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  8. 2024
    FusDom: Combining in-Domain and Out-of-Domain Knowledge for Continuous Self-Supervised LearningAshish Seth, Sreyan Ghosh, S. Umesh, Dinesh ManochaICASSP · Indian Institute of Technology Madras · University of Maryland, College Park
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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.