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 351–400Sort Recent · Most cited
  1. 2026
    Energy-Structured Low-Rank Adaptation for Continual LearningLonghua Li, Lei Qi, Qi Tian, Xin GengICML
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  5. 2026
    COVD: Continual Open-Vocabulary Object Detection with Novel Concept InjectionYupeng Zhang, Ruize Han, Yuzhong Feng … Liang WanarXiv
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  6. 2026
    ICICLE: Expanding Retrieval with In-Context DocumentsYu-Chen Den, Yung-Yu Shih, Zhi Rui Tam … Eugene YangarXiv
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  9. 2026
    The Future of Facts: Tracing the Factual Generation-Verification GapTim R. Davidson, Anja Surina, Caglar GulcehrearXiv
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  12. 2026
    PKTA: Part-oriented Knowledge Transfer and Acquisition for Non-Exemplar Lifelong Person Re-IdentificationRuixuan Gao, Qijun Zhao, Yangqianqian ChenIEEE International Conference on Automatic Face & Gesture…
  13. 2026
    Dynamic GNNs for Continual Learning on CircuitsRupesh Raj Karn, Johann Knechtel, Ozgur SinanogluIEEE International Symposium on Circuits and Systems (ISCAS) · New York University
  14. 2026PDF ↗
  15. 2026
    Parameter-Efficient Continuous Adaptation of Large Models in Hierarchical Federated NetworksWanrou Du, Yixuan Li, Xiaoqi Qin … Ping ZhangIEEE International Conference on Communications Workshops… · Beijing University of Posts and Telecommunications · State Key Laboratory of Networking and Switching Technology · +3
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  17. 2026
    TAAM:Inductive Graph-Class Incremental Learning with Task-Aware Adaptive ModulationJingtao Liu, Xi ZhangInternational Conference on Autonomous Agents and Multiag… · University of Science and Technology of China
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  18. 2026
    GSPA-3D: Geometric-Semantic Prototype Augmentation for 3D FSCILYuhang Ren, Shengwei Qin, Zhong LiAsia Conference on Computer Vision, Image Processing and… · Huzhou Normal University · Zhejiang University of Water Resource and Electric Power
  19. 2026
    Leveraging Information Flow for Knowledge Transfer in Continual LearningJoshua Andle, Ali Payani, Salimeh Yasaei-SekehNeural Processing Letters · University of Maine · Cisco Systems (China) · +1
  20. 2026PDF ↗
  21. 2026
    Mechanistic origins of catastrophic forgetting: why RL preserves circuits better than SFT?Jeanmely Rojas Nunez, Viraj Sawant, Nathan Allen … Maheep ChaudharyarXiv
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  22. 2026
    Dynamic Mixture of Latent Memories for Self-Evolving AgentsDianzhi Yu, Vireo Zhang, Hongru Wang … Irwin KingarXiv
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  23. 2026
    Continual Learning across multiple domains via a Dynamic Expandable and Mergeable ModelFei Ye, Ruilong Yu, Qihe Liu … Kun ZhangEng. Applications of AI · University of Electronic Science and Technology of China · University of York · +2
  24. 2026
    SeqLoRA: Bilevel Orthogonal Adaptation for Continual Multi-Concept GenerationJavad Parsa, Enis Simsar, Amir Joudaki … André TeixeiraarXiv
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  25. 2026
    Understanding Data Temporality Impact on Large Language Models Pre-trainingPilchen Hippolyte, Fabre Romain, Signe Talla Franck … Grave EdouardarXiv
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  26. 2026PDF ↗
  27. 2026
    Tunable MAGMAX: Preference-Aware Model Merging for Continual LearningKei Hiroshima, Kento Uchida, Shinichi ShirakawaICPR
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  28. 2026
    Continual Segmentation under Joint NonstationarityPrashant Pandey, Himanshu Kumar, Devineni Sri Venkatraya Chowdary, Brejesh LallICML
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  29. 2026PDF ↗
  30. 2026
    Fine-Tuning Without Forgetting via Loss-Adaptive Learning RatesParjanya Prashant, Jiongli Zhu, Aldan Creo, Babak SalimiarXiv
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  33. 2026
    Lifelong Learner: Discovering Versatile Neural Solvers for Vehicle Routing ProblemsShaodi Feng, Zhuoyi Lin, Jianan Zhou … Yew-Soon OngIEEE T-ITS · National Yang Ming Chiao Tung University · Agency for Science, Technology and Research · +2
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  34. 2026
    Learning When to AdaptAli Zindari, Xiaowen Jiang, Rotem Mulayoff, Sebastian U. SticharXiv
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  38. 2026
    Stable Routing for Mixture-of-Experts in Class-Incremental LearningZirui Guo, Quan Cheng, Da-Wei Zhou, Lijun ZhangarXiv
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  39. 2026
    CC-GFRT: Class Correlation-based Granular Feature Refinement and Transfer for Non-Exemplar Class Incremental LearningR. S. Gao, Zongyong Deng, Yue Yang, Qijun ZhaoKnowledge-Based Systems · Sichuan University · Sino Biological (China)
  40. 2026
    Reasoning Portability: Guiding Continual Learning for MLLMs in the RLVR Era红秋 何, Yuyang Liu, Shuo Yang … Yonghong TianarXiv
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  41. 2026
    MixSD: Mixed Contextual Self-Distillation for Knowledge InjectionJiarui Liu, Lechen Zhang, Yongjin Yang … Mona DiabarXiv
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  42. 2026PDF ↗
  43. 2026
    Randomized neural network with adaptive forward regularization for online task-free class incremental learningJunda Wang, Minghui Hu, Ning Li … Ponnuthurai Nagaratnam SuganthanNeural Networks · Shanghai Jiao Tong University · Nanyang Technological University · +1
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  44. 2026
    CLARE: Continual Learning for Vision-Language-Action Models via Autonomous Adapter Routing and ExpansionRalf Römer, Y Zhang, Yuming Li, Angela P. SchoelligRA-L · Technical University of Munich
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  45. 2026
    Continual Learning of Domain-Invariant RepresentationsPascal Janetzky, Tobias Schlagenhauf, Stefan FeuerriegelICML
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  46. 2026
    The organization of multiple motor memories.Daniel M. WolpertCurrent Opinion in Neurobiology · Allen Institute for Brain Science
  47. 2026
    Beyond catastrophic forgetting: A continual learning-driven multi-modal fusion model for saliency prediction in dynamic scenesNana Zhang, Yi-Xiang Wang, Dandan Zhu … Guangtao ZhaiExpert Systems with Applications · Donghua University · Tongji University · +1
  48. 2026
    Dynamic Prompt Synthesis Via Global Codebook Aggregation and Residual Compensation for Continual LearningYong Dai, Haijun Liu, Yingping Zhao, Jie YangInternational Symposium on Robotics, Artificial Intellige… · Shenzhen Polytechnic University · University of Science and Technology Liaoning
  49. 2026
  50. 2026
    Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?Mohammad Ali Vahedifar, Abhisek Ray, Qi ZhangICML
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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.