Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 6,984Sort Recent · Most cited
  1. 2025
    MoTiC: Momentum Tightness and Contrast for Few-Shot Class-Incremental LearningZeyu He, Shuai Huang, Yuwu Lu, Ming ZhaoPattern Recognition · Guilin University of Electronic Technology · South China Normal University
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  2. 2025
    Relation preserving for incremental image retrievalHongsong Wang, A. LiJournal of Electronic Imaging · South China Normal University
  3. 2025
    Enhancing Few-Shot Class-Incremental Learning via Cross-Modal Bias AlignmentD. Wang, Zhiming Chen, Xiang Qiu … Bingzhi ChenIEEE International Conference on Multimedia and Expo (ICME) · Beijing Institute of Technology · Zhuhai Institute of Advanced Technology · +2
  4. 2025
    Advancing Few-Shot Class-Incremental Learning with Virtual Prototype Guidance PromptingXiang Qiu, Huanjia Zhu, Xiaocheng Fang … Hui LinICASSP · South China Normal University
  5. 2025
    A2GP-SF: Enhancing Few-shot Class Incremental Learning via Attribute Generative Prompting and Adaptive Sharpness FlatteningZhiming Chen, De‐Shen Wang, Sisi Fu … Bingzhi ChenICASSP · South China Normal University
  6. 2025
    Towards Differential Optimization: Rehearsal-Free Class-Incremental Learning with Slow Learners and Fast AdaptersYinghong Chen, Huanjia Zhu, Jiali Cai … Bingzhi ChenICASSP · South China Normal University
  7. 2025
    Knowledge-guided prompt-based continual learning: Aligning task-prompts through contrastive hard negativesHengyang Lu, Lauren Lin, Chenyou Fan … Xiao‐Jun WuKnowledge-Based Systems · Jiangnan University · South China Normal University
  8. 2025
    Lifelong-MonoDepth: Lifelong Learning for Multidomain Monocular Metric Depth EstimationJunjie Hu, Chenyou Fan, Liguang Zhou … Tin Lun LamTNNLS · Chinese University of Hong Kong, Shenzhen · South China Normal University · +2
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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. 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.