Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

12 papers of 11,817Sort Recent · Most cited
  1. 2026
    Retrievable Gradients: Continual Post-Training Without Cumulative Weight DriftWeihang Su, Ji-Hun Kang, Jing-Yan Xu … Yiqun LiuarXiv
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  2. 2026
    Orchestrating Prompt Expertise: Enhancing Knowledge Distillation via Expert-Guided TuningXu Meng, Jun Rao, Shuhan Qi … Xuan WangACM Trans. Asian Low Resour. Lang. Inf. Process.
  3. 2026PDF ↗
  4. 2025
    Knowledge Fusion of Large Language Models Via Modular SkillPacksGuodong Du, Zhuo Li, Xuanning Zhou … Jing LiarXiv
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  5. 2025PDF ↗
  6. 2025PDF ↗
  7. 2025PDF ↗
  8. 2025
    Improving GenIR Systems Based on User FeedbackQingyao Ai, Zhicheng Dou, Min ZhangarXiv
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  9. 2025
    Continuous Knowledge-Preserving Decomposition for Few-Shot Continual LearningXiao-Jie Li, Yibo Yang, Jianlong Wu … Min ZhangarXiv
  10. 2025
    Boosting LLM’s Continual Sentiment Understanding for Low-Resource LanguagesHan Zhang, Jing-Jing Wang, Jia-Min Luo … Guo-Dong ZhouIEEE TASLP
  11. 2024PDF ↗
  12. 2024
    Why not transform chat large language models to non-English?Xiang Geng, Ming Zhu, Jiahuan Li … Shujian HuangFrontiers of Computer Science
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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 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.