{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T00:08:06Z","timestamp":1779235686071,"version":"3.51.4"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.asoc.2026.114601","type":"journal-article","created":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T04:48:08Z","timestamp":1768711688000},"page":"114601","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Non-exemplar class-incremental learning: Dynamic adversarial sample synthesis and relational knowledge distillation"],"prefix":"10.1016","volume":"191","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2112-6214","authenticated-orcid":false,"given":"Yuanlong","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoli","family":"Ke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.asoc.2026.114601_bib0005","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5871","article-title":"Prototype augmentation and self-supervision for incremental learning","author":"Zhu","year":"2021"},{"key":"10.1016\/j.asoc.2026.114601_bib0010","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9296","article-title":"Self-sustaining representation expansion for non-exemplar class-incremental learning","author":"Zhu","year":"2022"},{"key":"10.1016\/j.asoc.2026.114601_bib0015","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"3967","article-title":"Relational knowledge distillation","author":"Park","year":"2019"},{"key":"10.1016\/j.asoc.2026.114601_bib0020","series-title":"International Conference on Learning Representations (ICLR)","article-title":"Knowledge distillation via softmax regression representation learning","author":"Yang","year":"2021"},{"key":"10.1016\/j.asoc.2026.114601_bib0025","author":"Chaudhry"},{"key":"10.1016\/j.asoc.2026.114601_bib0030","author":"Riemer"},{"key":"10.1016\/j.asoc.2026.114601_bib0035","author":"Zhang"},{"key":"10.1016\/j.asoc.2026.114601_bib0040","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"3335","article-title":"Continual learning by asymmetric loss approximation with single-side overestimation","author":"Park","year":"2019"},{"key":"10.1016\/j.asoc.2026.114601_bib0045","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9001","article-title":"Continual learning with extended kronecker-factored approximate curvature","author":"Lee","year":"2020"},{"key":"10.1016\/j.asoc.2026.114601_bib0050","author":"Swaroop"},{"key":"10.1016\/j.asoc.2026.114601_bib0055","author":"Adel"},{"key":"10.1016\/j.asoc.2026.114601_bib0060","author":"Loo"},{"key":"10.1016\/j.asoc.2026.114601_bib0065","series-title":"International Conference on Machine Learning","first-page":"2621","article-title":"Kernel continual learning","author":"Derakhshani","year":"2021"},{"key":"10.1016\/j.asoc.2026.114601_bib0070","series-title":"International Conference on Machine Learning","first-page":"5290","article-title":"Variational auto-regressive Gaussian processes for continual learning","author":"Kapoor","year":"2021"},{"key":"10.1016\/j.asoc.2026.114601_bib0075","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"5339","article-title":"Overcoming catastrophic forgetting by neuron-level plasticity control","volume":"vol. 34","author":"Paik","year":"2020"},{"key":"10.1016\/j.asoc.2026.114601_bib0080","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"99","article-title":"Gcr: gradient coreset based replay buffer selection for continual learning","author":"Tiwari","year":"2022"},{"key":"10.1016\/j.asoc.2026.114601_bib0085","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9634","article-title":"Layerwise optimization by gradient decomposition for continual learning","author":"Tang","year":"2021"},{"key":"10.1016\/j.asoc.2026.114601_bib0090","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11371","article-title":"Class-incremental exemplar compression for class-incremental learning","author":"Luo","year":"2023"},{"key":"10.1016\/j.asoc.2026.114601_bib0095","author":"Ramesh"},{"issue":"12","key":"10.1016\/j.asoc.2026.114601_bib0100","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1038\/s42256-023-00747-w","article-title":"Incorporating neuro-inspired adaptability for continual learning in artificial intelligence","volume":"5","author":"Wang","year":"2023","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.asoc.2026.114601_bib0105","series-title":"European Conference on Computer Vision","first-page":"254","article-title":"Coscl: cooperation of small continual learners is stronger than a big one","author":"Wang","year":"2022"},{"key":"10.1016\/j.asoc.2026.114601_bib0110","first-page":"14374","article-title":"Meta-consolidation for continual learning","volume":"33","author":"Kj","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.asoc.2026.114601_bib0115","first-page":"14135","article-title":"Posterior meta-replay for continual learning","volume":"34","author":"Henning","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.asoc.2026.114601_bib0120","series-title":"International Conference on Learning Representations","article-title":"Overcoming catastrophic forgetting for continual learning via model adaptation","author":"Hu","year":"2019"},{"key":"10.1016\/j.asoc.2026.114601_bib0125","author":"Von Oswald"},{"issue":"13","key":"10.1016\/j.asoc.2026.114601_bib0130","doi-asserted-by":"crossref","first-page":"3521","DOI":"10.1073\/pnas.1611835114","article-title":"Overcoming catastrophic forgetting in neural networks","volume":"114","author":"Kirkpatrick","year":"2017","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"12","key":"10.1016\/j.asoc.2026.114601_bib0135","doi-asserted-by":"crossref","first-page":"2935","DOI":"10.1109\/TPAMI.2017.2773081","article-title":"Learning without forgetting","volume":"40","author":"Li","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.asoc.2026.114601_bib0140","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"2001","article-title":"Icarl: incremental classifier and representation learning","author":"Rebuffi","year":"2017"},{"key":"10.1016\/j.asoc.2026.114601_bib0145","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1016\/j.neunet.2023.05.006","article-title":"Multi-granularity knowledge distillation and prototype consistency regularization for class-incremental learning","volume":"164","author":"Shi","year":"2023","journal-title":"Neural Networks"},{"key":"10.1016\/j.asoc.2026.114601_bib0150","author":"Hinton"},{"key":"10.1016\/j.asoc.2026.114601_bib0155","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11953","article-title":"Decoupled knowledge distillation","author":"Zhao","year":"2022"},{"key":"10.1016\/j.asoc.2026.114601_bib0160","series-title":"International Conference on Machine Learning","first-page":"24031","article-title":"Self-supervised models are good teaching assistants for vision transformers","author":"Wu","year":"2022"},{"key":"10.1016\/j.asoc.2026.114601_bib0165","author":"Bai"},{"key":"10.1016\/j.asoc.2026.114601_bib0170","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"233","article-title":"End-to-end incremental learning","author":"Castro","year":"2018"},{"issue":"11","key":"10.1016\/j.asoc.2026.114601_bib0175","doi-asserted-by":"crossref","first-page":"4037","DOI":"10.1109\/TPAMI.2020.2992393","article-title":"Self-supervised visual feature learning with deep neural networks: a survey","volume":"43","author":"Jing","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.asoc.2026.114601_bib0180","series-title":"Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, the Netherlands, October 11\u201314, 2016, Proceedings, Part IV 14","first-page":"577","article-title":"Learning representations for automatic colorization","author":"Larsson","year":"2016"},{"key":"10.1016\/j.asoc.2026.114601_bib0185","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"132","article-title":"Deep clustering for unsupervised learning of visual features","author":"Caron","year":"2018"},{"key":"10.1016\/j.asoc.2026.114601_bib0190","first-page":"9912","article-title":"Unsupervised learning of visual features by contrasting cluster assignments","volume":"33","author":"Caron","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.asoc.2026.114601_bib0195","author":"Gidaris"},{"key":"10.1016\/j.asoc.2026.114601_bib0200","series-title":"International Conference on Machine Learning","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"Chen","year":"2020"},{"key":"10.1016\/j.asoc.2026.114601_bib0205","series-title":"International Conference on Machine Learning","first-page":"5714","article-title":"Self-supervised label augmentation via input transformations","author":"Lee","year":"2020"},{"key":"10.1016\/j.asoc.2026.114601_bib0210","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XXVI 16","first-page":"699","article-title":"More classifiers, less forgetting: a generic multi-classifier paradigm for incremental learning","author":"Liu","year":"2020"},{"key":"10.1016\/j.asoc.2026.114601_bib0215","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6982","article-title":"Semantic drift compensation for class-incremental learning","author":"Yu","year":"2020"},{"key":"10.1016\/j.asoc.2026.114601_bib0220","series-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Learning a unified classifier incrementally via rebalancing","author":"Hou","year":"2019"},{"key":"10.1016\/j.asoc.2026.114601_bib0225","series-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"issue":"7","key":"10.1016\/j.asoc.2026.114601_bib0230","first-page":"3","article-title":"Tiny imagenet visual recognition challenge","volume":"7","author":"Le","year":"2015","journal-title":"CS 231N"},{"key":"10.1016\/j.asoc.2026.114601_bib0235","series-title":"2009 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"248","article-title":"Imagenet: a large-scale hierarchical image database","author":"Deng","year":"2009"},{"key":"10.1016\/j.asoc.2026.114601_bib0240","series-title":"IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"1772","article-title":"Prototype reminiscence and augmented asymmetric knowledge aggregation for non-exemplar class-incremental learning","author":"Shi","year":"2023"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626000499?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626000499?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T23:26:20Z","timestamp":1779233180000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626000499"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":48,"alternative-id":["S1568494626000499"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.114601","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Non-exemplar class-incremental learning: Dynamic adversarial sample synthesis and relational knowledge distillation","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.114601","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114601"}}