Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 6,984Sort Recent · Most cited
  1. 2025
    Continual Learning for Multilingual Neural Machine Translation via Meta-Contrastive Memory ReplayLin Zhou, Degen Huang, Junpeng Liu … Kaiyu HuangSpringer LNCS · Dalian University of Technology · Université de Montréal · +1
  2. 2025
    Federated Class-Incremental Learning with New-Class Augmented Self-DistillationZhiyuan Wu, Tianliu He, Sheng Sun … Xuefeng JiangJournal of Computer Science and Technology · Chinese Academy of Sciences · Institute of Computing Technology · +2
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  3. 2025
    Online Versatile Incremental Learning via BiPromptHailun Zeng, Baopeng Zhang, Teng Zhu, Yuanzhouhan CaoInternational Symposium on Intelligent Robotics and Syste… · Beijing Jiaotong University
  4. 2025
    CoMBO: Conflict Mitigation via Branched Optimization for Class Incremental SegmentationKai Fang, Anqi Zhang, Guangyu Gao … Yunchao WeiCVPR · Beijing Institute of Technology · University of Birmingham · +1
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  5. 2025
    AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view ClusteringJing Wang, Songhe Feng, Kristoffer Wickstrøm, Michael KampffmeyerCVPR · Beijing Jiaotong University · UiT The Arctic University of Norway
  6. 2025
    LAGD: Local Topological-Alignment and Global Semantic-Deconstruction for Incremental 3D Semantic SegmentationYumin Zhang, Haoran Duan, Rui Sun … Bo WeiAAAI · Newcastle University · Beijing Jiaotong University
  7. 2025
    Multi-Stage LLM Fine-Tuning with a Continual Learning SettingChanghao Guan, Chao Huang, Hongliang Li … Jian LiuNAACL · Beijing Jiaotong University · University of Science and Technology Beijing
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  8. 2025
    CCKA: Continual Cross-Domain Knowledge Adaptation for Multi-Domain Machine TranslationZhibo Man, Yujie Zhang, Yuanmeng Chen … Jinan XuIEEE Transactions · Beijing Jiaotong University
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. 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.