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.

1,140 papers of 7,070 · showing 451–500Sort Recent · Most cited
  1. 2026
    Predicting Plasticity in Deep Continual Learning: A Theoretical PerspectiveJiuqi Wang, Jayanth Srinivasa, Claire Chen … Shangtong ZhangarXiv
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  2. 2026
    Cross-Sample Relational Fusion: Unifying Domain Generalization and Class-Incremental LearningZhenghe Xie, Yan Wang, Hao Sun … Da-Wei ZhouIEEE Trans. Multimedia
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  3. 2026
    CogniSNN: Enabling neuron-expandability, pathway-reusability, and dynamic-configurability in spiking neural networksYongsheng Huang, Peibo Duan, Yujie Wu … Mingkun XuNeural Networks · Northeastern University · Hong Kong Polytechnic University · +2
  4. 2026
    Preserving Foundational Capabilities in Flow-Matching VLAs through Conservative SFTTianyi Zhang, Shaopeng Zhai, Haoran Zhang … Qi ZhangarXiv
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  9. 2026
    SAILS: Segment Anything with Incrementally Learned Semantics for Task-Invariant and Training-Free Continual LearningShishir Muralidhara, Didier Stricker, René SchusterIEEE Conference on Artificial Intelligence (CAI) · German Research Centre for Artificial Intelligence
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  11. 2026
    Characterizing continual learning scenarios and strategies for audio analysisRuchi Bhatt, Pratibha Kumari, Dwarikanath Mahapatra … Mukesh SainiEURASIP Journal on Audio Speech and Music Processing
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  13. 2026
    CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual LearningMd Anwar Hossen, Fatema Siddika, J. Pablo Muñoz … Ali JannesariarXiv
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  14. 2026
    Gated subspace alignment with drift compensation for parameter-efficient Class-Incremental Learning顾建业, Shucheng Huang, Tian Li … Mingxing LiPLOS · Jiangsu University of Science and Technology · Suzhou University of Science and Technology · +1
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  16. 2026
    Skill Neologisms: Towards Skill-based Continual LearningAntonin Berthon, Nicolás Astorga, Mihaela van der SchaarICML
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  18. 2026
    Attribution-Guided Continual Learning for Large Language ModelsYazheng Liu, Yuxuan Wan, Rui Xu … Hui XiongarXiv
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  19. 2026
    ComAdPro: compositional learning with prototype adaptation for logo few-shot class-incremental recognition (ChinaMM 2025)Jianxin Zhan, 陈文泰, Sujuan Hou, Weiqing MinMultimedia Systems · Shandong Normal University · Chinese Academy of Sciences · +1
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  22. 2026
    Stabilizing LLM Supervised Fine-Tuning via Explicit Distributional ControlXinyu Wang, Changzhi Sun, Yuanbin Wu, Xiaoling WangarXiv
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  23. 2026
    Federated Class Incremental Learning Method With High Accuracy and Extremely Low Communication Cost Based on Broad Learning SystemJie Du, Wenbing Chen, Peng Liu … C L Philip ChenIEEE Transactions · Shenzhen University · University of Electronic Science and Technology of China · +2
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  25. 2026
    Memory-Efficient Continual Learning with CLIP ModelsRyan King, Gang Li, Bobak Mortazavi, Tianbao YangarXiv
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  26. 2026
    Sharpness-Aware Pretraining Mitigates Catastrophic ForgettingIshaan Watts, Catherine Li, Sachin Goyal … Aditi RaghunathanarXiv
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  27. 2026
    Elastic Multi-Gradient Descent for Parallel Continual LearningFan Lyu, Wei Feng, Yuepan Li … Liang WangTPAMI · Universitat Autònoma de Barcelona · Tianjin University · +2
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  28. 2026
    Learning forward-compatible and domain-invariant representations for cross-domain few-shot class-incremental learningWeidong Shi, Xudong Yan, Jiazheng Yuan … Songhe FengNeural Networks · Beijing Jiaotong University · Beijing Normal University · +3
  29. 2026
    Sparse Memory Finetuning as a Low-Forgetting Alternative to LoRA and Full FinetuningPrakhar Gupta, Garv Shah, Satyam Goyal, Anirudh KanchiarXiv
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  34. 2026
    Scalable Expansion of Multilingual Speech LLMs for ASR: A Continual Learning ApproachLorenzo Concina, Marco Matassoni, Alessio BruttiLanguage Resources and Evaluation Conference · Fondazione Bruno Kessler
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  35. 2026
    Decouple before Integration: Test-time Synthesis of SFT and RLVR Task VectorsChaohao Yuan, Chenghao Xiao, Yu Rong … Long-Kai HuangarXiv
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  36. 2026
    Deep Continual Learning: Survey of Method and ApplicationYigong Wang, Zhuoyi Wang, Mu-Fan Sang … Latifur KhanIEEE International Conference on Big Data Security on Cloud
  37. 2026
    Forager: a lightweight testbed for continual learning with partial observability in RLSteven Tang, Xinze Xiong, Anna Hakhverdyan … Adam WhitearXiv
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  38. 2026
    Text-guided class-incremental point cloud semantic segmentation with category distribution constraintChao Zheng, Yan Xu, Xiaorui Peng … Yu MengEng. Applications of AI · University of Science and Technology Beijing
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  41. 2026
    Learning to Forget: Continual Learning with Adaptive Weight DecayAditya A. Ramesh, Alex Lewandowski, Jürgen SchmidhuberarXiv
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  42. 2026
    NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual LearningKarthik Raghunathan, Christian Metzner, Laura Kriener, Melika PayvandarXiv
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  43. 2026PDF ↗
  44. 2026
    Continual Test-Time Training on Graphs via Adaptive Prompts IntegrationQianyi Cai, Ziyue Qiao, Rui Cai … Hui XiongTPAMI · Great Bay University · University of California, Davis · +2
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  47. 2026
    CLEAR-BART: A Continuous Learning Architecture for Informal Text Transformation in the GenZ Social Information AgeNandhini Shanmugarajah, Lu Liu, Zeyu Fu, Yuchen ZhangInternational Conference on Multi-scale Artificial Intell… · University of Exeter · University of Essex
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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 written 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.