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.

6,984 papers · showing 101–150Sort Recent · Most cited
  1. 2026
    An active-learning framework for real-time depth perception from monocular vision streamsXiaorong Zeng, Weiqiang Chen, Peng Shi … Shuiwen ShenarXiv
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  2. 2026PDF ↗
  3. 2026
    NeuMoSync: End‑to‑End Neuromodulatory Control for Plasticity and Adaptability in Continual LearningSeyed Roozbeh Razavi Rohani, Khashayar Khajavi, Wesley Chung … Mo ChenTMLR
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  4. 2026
    Self-adaptive Low-Rank Adaptation for Class-Incremental LearningYiming Song, Qiqi Duan, Lijun Sun … Yuhui ShiSpringer LNCS · Southern University of Science and Technology · Jiangxi University of Finance and Economics · +3
  5. 2026
    A lightweight and reliable continual learning framework for lip-readingZhixue Chen, Changyan Zheng, Yakun Zhang … Erwei YinDisplays · University of Electronic Science and Technology of China · Academy of Military Medical Sciences · +2
  6. 2026PDF ↗
  7. 2026
    Field-Aware Agent Skill RetrievalPaimon Goulart, Liang Wu, Kelly Wan … Liangjie HongarXiv
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  8. 2026
    Learning What to Remember: Test-Time Training via Context DistillationZixuan Wang, Xingyu Dang, Rui-Jie Zhu … Jason D. LeearXiv
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  9. 2026
  10. 2026
    Research on anti-forgetting training strategies for open-vocabulary object detection systemsYujia He, Jianshe Dong, Jiayu LinICCV · Tianjin University of Technology and Education
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  12. 2026
    Counterfactual distribution intervention for few-shot class-incremental learningJicheng Yuan, Wenfa Li, Lusi Li … Xin NingKnowledge-Based Systems · Chinese Academy of Sciences · Institute of Semiconductors · +2
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  15. 2026
    TriP: A triple-prompt framework aligning pre-training and class-incremental objectives in continual graph learning.Can-Ming Cui, Hui-yu Zhou, Pei-Yuan Lai, Chang‐Dong WangNeural Networks · Sun Yat-sen University · Guangxi Zhuang Autonomous Region Health and Family Planning · +1
  16. 2026
    Dream2Learn: Structured Generative Dreaming for Continual LearningSalvatore Calcagno, Matteo Pennisi, Federica Proietto Salanitri … Giovanni BellittoIJCV · University of Catania
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  17. 2026
    Relative Parameter Importance in Task-Agnostic Replay-Free Continual LearningMalavika Suresh, Ikechukwu Nkisi-Orji, Nirmalie WiratungaarXiv
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  18. 2026
    Spontaneous emergence of context-dependent statistical learning in humans and neural networksFleming Peck, Hongjing Lu, Jesse RissmaniScience · University of California, Los Angeles · Neurobehavioral Systems
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  19. 2026
    The Grokked Illusion: True Equilibrium Mitigates Catastrophic ForgettingXiaotian Zhang, Lai Shun Chan, Yue Shang … Ge ZhangarXiv
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  24. 2026
    FSE: Continual learning for named entity recognition by fast-slow expertsYunan Zhang, Yang Fan, Heng Li … Qingcai ChenPattern Recognition Letters
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  25. 2026
    SPGNet: Spectral Prototype Generation for balancing the memory-structure dilemma in graph continual learningYanfeng Sun, Binbin Chen, Shaofan WangDisplays · Beijing University of Technology
  26. 2026PDF ↗
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  28. 2026
    MemSFT: Mitigating Alignment Tax with an External Parametric MemoryJiarui Wang, Xiang Shi, Jiaqi Cao … Zhouhan LinarXiv
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  29. 2026PDF ↗
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  31. 2026
    Metaplasticity as adaptive gradient preconditioning for incremental learningIsabelle Aguilar, Zayn Andre Zainal, Omid KaveheiarXiv
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  32. 2026
    Bi-Compatible Task-Agnostic Feature Augmentation for Expansion-Based Class-Incremental LearningBowen Zheng, Zijun Shen, Da-Wei Zhou … De‐Chuan ZhanIJCV · Nanjing University
  33. 2026
    In Situ Training of Implicit Neural Compressors for Scientific Simulations via Sketch-Based RegularizationCooper Simpson, Stephen Becker, Alireza DoostanJournal of Computational Physics · University of Colorado Boulder · University of Washington Applied Physics Laboratory · +2
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  34. 2026
    Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual LearningReza Rahimi Azghan, Gautham Krishna Gudur, Giulia Pedrielli … Hassan GhasemzadeharXiv
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  35. 2026PDF ↗
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  38. 2026
    Spectral-Aware Analytic Class-Incremental Learning for Long-Tailed DistributionsQ. Tran, Ngoc-Hai Nguyen, Quan Dao … Dimitris N. MetaxasarXiv
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  39. 2026
    Adaptive Multi-Horizon Reinforcement LearningManoosh Samiei, Doina Precup, Paul MassetarXiv
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  40. 2026
    Continual Video-MLLM Adaptation over Evolving DomainsRui Cheng, Meixing Shi, Yuxiang Cai … Zhi X. ChenarXiv
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  41. 2026
    TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time SeriesG. Szücs, Samuel Jacsev, Marcell Németh … Gian Antonio SustoarXiv
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  42. 2026
    TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time SeriesGábor Szűcs, Sámuel Jacsev, Marcell Németh … Gian Antonio SustoarXiv · Budapest University of Technology and Economics · University of Padua
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  43. 2026
    Rethinking Transfer in Continual Learning: A Replay-Based RealisationYang Meng, Zhenya Liu, Zhuokai Zhao, Yuxin ChenarXiv
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  44. 2026PDF ↗
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  46. 2026
  47. 2026
    Prototype Replay for Cold-Start Online Class-Incremental Learning in Spiking NetworksFatima Tuz Zohora, Dhireesha KudithipudiInternational Conference on Neuromorphic Systems · The University of Texas at San Antonio
  48. 2026
    Sleep-Inspired Replay-Driven Online Temporal Learning with Memristive Neuromorphic Hardware for Edge SystemsSree Nirmillo Biswash Tushar, Sk. Hasibul Alam, Miranda Gonzales … Garrett S. RoseInternational Conference on Neuromorphic Systems · University of Tennessee at Knoxville · The University of Texas at San Antonio
  49. 2026
    The write-cost bottleneck: energy constraints on continual learning in brains and machinesBingru Xu, Hao Shen, Yuguo YuCognitive Neurodynamics · Shanghai Center for Brain Science and Brain-Inspired Technology
  50. 2026
    Parameter-Efficient Continual Fine-Tuning: A SurveyE N Coleman, Luigi Quarantiello, Ziyue Liu … Vincenzo LomonacoNeurocomputing · University of Pisa · Politecnico di Torino · +4
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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 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.