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.

7 papers of 8,653Sort Recent · Most cited
  1. 2024
    Distribution-Level Memory Recall for Continual Learning: Preserving Knowledge and Avoiding ConfusionShaoxu Cheng, Kanglei Geng, Chiyuan He … Hongliang LiIEEE Trans. Multimedia · University of Electronic Science and Technology of China
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  2. 2024
    Class Incremental Learning with Multi-Teacher DistillationHaitao Wen, Lili Pan, Yu Dai … Hongliang LiCVPR · University of Electronic Science and Technology of China
  3. 2024
    Dual-Consistency Model Inversion for Non-Exemplar Class Incremental LearningZihuan Qiu, Yi Xu, Fanman Meng … Qingbo WuCVPR · University of Electronic Science and Technology of China · Dalian University of Technology
  4. 2024
    Continual Egocentric Activity Recognition With Foreseeable-Generalized Visual–IMU RepresentationsChi-Yuan He, Shaoxu Cheng, Zi-Huan Qiu … Hongliang LiIEEE Sensors Journal
  5. 2024
    Vision-Sensor Attention Based Continual Multimodal Egocentric Activity RecognitionShaoxu Cheng, Chi-Yuan He, Kailong Chen … Qingbo WuICASSP
  6. 2024
    Continual Cross-Domain Image Compression via Entropy Prior Guided Knowledge Distillation and Scalable DecodingChenhao Wu, Qingbo Wu, Rui Ma … Heqian QiuIEEE TCSVT · University of Electronic Science and Technology of China
  7. 2024
    InfoUCL: Learning Informative Representations for Unsupervised Continual LearningLiang Zhang, Jiangwei Zhao, Qingbo Wu … Hongliang LiIEEE Trans. Multimedia · University of Electronic Science and Technology of China
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 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.