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. 2026
    Retrievable Gradients: Continual Post-Training Without Cumulative Weight DriftWeihang Su, Jiacheng Kang, Jingyan Xu … Yiqun LiuarXiv
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  2. 2026
    Why not transform chat large language models to non-English?Xiang Geng, Ming Zhu, Jiahuan Li … Shujian HuangFrontiers of Computer Science · Nanjing University · Huawei Technologies (China)
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  3. 2025PDF ↗
  4. 2025
    Knowledge Fusion of Large Language Models Via Modular SkillPacksGuodong Du, Zhuo Li, Zhou, Xuanning … Jing LiarXiv
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  5. 2025PDF ↗
  6. 2025
    CMT: A Memory Compression Method for Continual Knowledge Learning of Large Language ModelsDongfang Li, Zetian Sun, Xinshuo Hu … Min ZhangAAAI · Harbin Institute of Technology
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  7. 2025PDF ↗
  8. 2024PDF ↗
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.