Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

240 papers of 8,653 · showing 51–100Sort Recent · Most cited
  1. 2024
    Accurate Forgetting for Heterogeneous Federated Continual LearningAbudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang … Masashi SugiyamaICLR
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  5. 2025
    Spurious Forgetting in Continual Learning of Language ModelsJunhao Zheng, Cai, Xidi, Shengjie Qiu, Qianli MaICLR
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  6. 2025
    SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental LearningYichen Wu, Hongming Piao, Long-Kai Huang … Ying WeiICLR
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  7. 2025
    C-CLIP: Multimodal Continual Learning for Vision-Language ModelWenzhuo Liu, Fei Zhu, Longhui Wei, Qi TianICLR
  8. 2025
    Coreset Selection via Reducible Loss in Continual LearningRuilin Tong, Yuhang Liu, J. Shi, Dong GongICLR
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  11. 2025
    Boosting Multiple Views for pretrained-based Continual LearningQ. Tran, T. Tran, Khanh Doan … Trung LeICLR
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  13. 2025
    Semantic Aware Representation Learning for Lifelong LearningFahad Sarfraz, Elahe Arani, Bahram ZonoozICLR
  14. 2025
    Federated Few-Shot Class-Incremental LearningM. A. Ma'sum, Mahardhika Pratama, Lin Liu … Ryszard KowalczykICLR
  15. 2025
    Vision and Language Synergy for Rehearsal Free Continual LearningM. A. Ma'sum, Mahardhika Pratama, Savitha Ramasamy … Ryszard KowalczykICLR
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  22. 2025
    Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline DataZhiyuan Zhou, Peng, Andy, Qiyang Li … Aviral KumarICLR
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  25. 2025
    Plastic Learning with Deep Fourier FeaturesAlex Lewandowski, Dale Schuurmans, Marlos C. MachadoICLR
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  27. 2025
    Closed-form merging of parameter-efficient modules for Federated Continual LearningRiccardo Salami, Pietro Buzzega, Matteo Mosconi … Simone CalderaraICLR
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  28. 2025
    LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model MergingKe Wang, Nikolaos Dimitriadis, Alessandro Favero … Pascal FrossardICLR
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  31. 2025
    Adapt-∞: Scalable Continual Multimodal Instruction Tuning via Dynamic Data SelectionAdyasha Maharana, Jaehong Yoon, Tianlong Chen, Mohit BansalICLR
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  32. 2025
    Neuroplastic Expansion in Deep Reinforcement LearningJiashun Liu, Johan Obando-Ceron, Aaron Courville, Ling PanICLR
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  33. 2025
    LeanAgent: Lifelong Learning for Formal Theorem ProvingAdarsh Kumarappan, Mohit Tiwari, Peiyang Song … Anima AnandkumarICLR
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  35. 2025
    Self-Updatable Large Language Models by Integrating Context into Model ParametersYu Wang, Xinshuang Liu, Xiusi Chen … Julian McAuleyICLR
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  36. 2025
    LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual LearningLiangzu Peng, Juan Elenter, Joshua Agterberg … René Víctor Valqui VidalICLR
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  39. 2025
    Theory on Mixture-of-Experts in Continual LearningHongbo Li, Sen Lin, Lingjie Duan … Ness B. ShroffICLR
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  40. 2025
    MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object DetectionZhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh … Yadan LuoICLR
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  41. 2025
    Towards Continuous Reuse of Graph Models via Holistic Memory DiversificationZiyue Qiao, Junren Xiao, Qingqiang Sun … Xiong, HuiICLR
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  42. 2025
    Learning Continually by Spectral RegularizationAlex Lewandowski, Bortkiewicz, Michał, Saurabh Kumar … Marlos C. MachadoICLR
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  44. 2025
    Perturbation-Restrained Sequential Model EditingJun-Yu Ma, Hong Wang, Hao-Xiang Xu … Jia-Chen GuICLR
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  45. 2025
    A Second-Order Perspective on Model Compositionality and Incremental LearningAngelo Porrello, Lorenzo Bonicelli, Pietro Buzzega … Rita CucchiaraICLR
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  46. 2025
    Adaptive Retention&Correction: Test-Time Training for Continual LearningHao Chen, Micah Goldblum, Zuxuan Wu, Yu–Gang JiangICLR
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  49. 2024
    Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained ComputationWenxuan Zhang, Youssef Mohamed, Bernard Ghanem … Mohamed ElhoseinyICLR
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  50. 2024
    Scalable Language Model with Generalized Continual LearningBohao Peng, Zhuotao Tian, Shu Liu … Jiaya JiaICLR
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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. By default it shows the 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. The rest are one click away under “All papers”. 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.