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.

5 papers of 4,574Sort Recent · Most cited
  1. 2023PDF ↗
  2. 2023
    Continual Learning for Generative Retrieval over Dynamic CorporaJiangui Chen, Ruqing Zhang, Jiafeng Guo … Xueqi ChengCIKM · University of Chinese Academy of Sciences · Amsterdam University of the Arts · +1
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  3. 2023
    Task Relation Distillation and Prototypical Pseudo Label for Incremental Named Entity RecognitionDuzhen Zhang, Hongliu Li, Wei Wei Cong … Xiuyi ChenCIKM · Baidu (China) · Hong Kong Polytechnic University · +3
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  4. 2023
    L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible RepresentationsYinqiong Cai, Keping Bi, Yixing Fan … Xueqi ChengCIKM · University of Chinese Academy of Sciences
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  5. 2023
    Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental LearningAnton Lee, Yaqian Zhang, Heitor Murilo Gomes … Bernhard PfahringerCIKM · Victoria University of Wellington · University of Waikato
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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.