Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

16 papers of 8,653Sort Recent · Most cited
  1. 2026
    Learning from imperfect data: incremental learning and Few-shot LearningYaoyao LiuAAAI · University of Illinois Urbana-Champaign
    PDF ↗
  2. 2025
    A rate-dependent coreset selector for continual learning on time-varying data distributionsZilin Luo, Zichen Tian, Yaoyao Liu, Qianru SunNeurocomputing · Singapore Management University · University of Illinois Urbana-Champaign
  3. 2026
    Rethinking softmax in incremental learningZheng Zhai, Jiali Zhang, Haiyu Wang … Qiang SunNeural Networks · Beijing Normal-Hong Kong Baptist University · Beijing Normal University · +4
  4. 2025
    Ferret: An Efficient Online Continual Learning Framework under Varying Memory ConstraintsYuhao Zhou, Yuxin Tian, Jindi Lv … Jiancheng LvCVPR · Sichuan University · National University of Singapore · +3
    PDF ↗
  5. 2024
    Anytime Continual Learning for Open Vocabulary ClassificationZhen Zhu, Yiming Gong, Derek HoiemECCV · University of Illinois Urbana-Champaign
    PDF ↗
  6. 2024
    SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial UnderstandingHaoxiang Wang, Pavan Kumar Anasosalu Vasu, Fartash Faghri … Hadi PouransariCVPR · University of Illinois Urbana-Champaign · Apple (United Kingdom)
    PDF ↗
  7. 2024
    Wakening Past Concepts without Past Data: Class-Incremental Learning from Online PlacebosYaoyao Liu, Yingying Li, Bernt Schiele, Qianru SunWACV · Johns Hopkins University · Max Planck Institute for Informatics · +2
    PDF ↗
  8. 2024
    Non-compositional Expression Generation and its Continual LearningJianing Zhou, Suma BhatACL · University of Illinois Urbana-Champaign
    PDF ↗
  9. 2023
    Do Pre-trained Models Benefit Equally in Continual Learning?Kuan-Ying Lee, Yuanyi Zhong, Yu-Xiong WangWACV · University of Illinois Urbana-Champaign
    PDF ↗
  10. 2022
    Learning Representations for New Sound Classes With Continual Self-Supervised LearningZhepei Wang, Cem Subakan, Xilin Jiang … Paris SmaragdisIEEE Signal Processing Letters · University of Illinois Urbana-Champaign · Concordia University · +2
    PDF ↗
  11. 2021
    Lifelong Event Detection with Knowledge TransferPengfei Yu, Heng Ji, Prem NatarajanEMNLP · University of Illinois Urbana-Champaign · Amazon (United States)
    PDF ↗
  12. 2020
    Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversionHongxu Yin, Pavlo Molchanov, Jose M. Álvarez … Jan KautzCVPR · Princeton University · University of Illinois Urbana-Champaign
    PDF ↗
  13. 2020
    Memory-Efficient Incremental Learning Through Feature AdaptationAhmet İşcen, Jeffrey Zhang, Svetlana Lazebnik, Cordelia SchmidECCV · University of Illinois Urbana-Champaign
    PDF ↗
  14. 2019
    Continual Learning of New Sound Classes Using Generative ReplayZhepei Wang, Cem Subakan, Efthymios Tzinis … Laurent CharlinIEEE Workshop on Applications of Signal Processing to Aud… · University of Illinois Urbana-Champaign · Mila - Quebec Artificial Intelligence Institute
    PDF ↗
  15. 2018
    PackNet: Adding Multiple Tasks to a Single Network by Iterative PruningArun Mallya, Svetlana LazebnikCVPR · University of Illinois Urbana-Champaign
    PDF ↗
  16. 2009
    The dark side of incremental learning: A model of cumulative semantic interference during lexical access in speech productionGary M. Oppenheim, Gary S. Dell, Myrna F. SchwartzCognition · University of Illinois Urbana-Champaign · Urbana University · +1
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. By default it shows the 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. The rest are one click away under “All papers”. 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.