{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T20:06:59Z","timestamp":1780603619569,"version":"3.54.1"},"reference-count":114,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Open J. Comput. Soc."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/ojcs.2026.3692927","type":"journal-article","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T19:45:19Z","timestamp":1779392719000},"page":"1083-1105","source":"Crossref","is-referenced-by-count":0,"title":["Pruning Strategies of Vision Transformers: A Specialized Survey"],"prefix":"10.1109","volume":"7","author":[{"given":"Setareh","family":"Ahsaei","sequence":"first","affiliation":[{"name":"School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7113-5197","authenticated-orcid":false,"given":"Mohsen","family":"Raji","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1002\/pmic.202300011"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3586074"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2021.3137383"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2010.11929"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/tai.2023.3326795"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3392941"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/tpds.2022.3222765"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/app122010227"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/tmc.2023.3315138"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/tcsvt.2023.3260310"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3403844"},{"key":"ref12","article-title":"Linformer: Self-attention with linear complexity","author":"Wang","year":"2020"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref14","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"Proc. Mach. Learn. Res.","author":"Touvron","year":"2021"},{"key":"ref15","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/lpt.2023.3342631"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3447085"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2023.3334614"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.07.045"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3934\/era.2022192"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2023.102990"},{"key":"ref22","article-title":"A survey on transformer compression","author":"Tang","year":"2024"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2024.103247"},{"key":"ref24","article-title":"Knowledge distillation in vision transformers: A critical review","author":"Habib","year":"2023"},{"key":"ref25","article-title":"Model quantization and hardware acceleration for vision transformers: A comprehensive survey","author":"Du","year":"2024"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/itsc55140.2022.9921989"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.62836\/jitp.v1i1.156"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i3.25461"},{"key":"ref29","article-title":"Cp-vit: Cascade vision transformer pruning via progressive sparsity prediction","author":"Song","year":"2022"},{"issue":"2","key":"ref30","first-page":"96","article-title":"A new approach for image classification: Convolutional neural network","volume":"6","author":"Cengil","year":"2016","journal-title":"Eur. J. Techn."},{"key":"ref31","first-page":"11960","article-title":"Not all images are worth 1616 words: Dynamic transformers for efficient image recognition","volume-title":"Proc. Adv. Neural Inf. Process Syst.","volume":"34","author":"Wang","year":"2021"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref33","article-title":"CTA-Net: A CNN-transformer aggregation network for improving multi-scale feature extraction","author":"Meng","year":"2024"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.52202\/068431-0655"},{"key":"ref35","first-page":"71586","article-title":"Probabilistic neural pruning via sparsity evolutionary fokker-planck-kolmogorov equation","volume-title":"Proc. Int. Conf. Learn. Representations","volume":"2025","author":"Mo","year":"2025"},{"key":"ref36","article-title":"Vision transformer: Vit and its derivatives","author":"Fu","year":"2022"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-022-3646-6"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/tcad.2021.3064914"},{"key":"ref39","article-title":"Escoin: Efficient sparse convolutional neural network inference on gpus","author":"Chen","year":"2018"},{"key":"ref40","article-title":"oViT: An accurate second-order pruning framework for vision transformers","author":"Kuznedelev","year":"2022"},{"key":"ref41","first-page":"598","article-title":"Optimal brain damage, advances in neural information processing systems","volume-title":"Denver 1989","volume":"598","author":"Le Cun","year":"1990"},{"key":"ref42","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.4529273","article-title":"Sparse then prune: Toward efficient vision transformers","author":"Prasetyo","year":"2023"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2025.103623"},{"key":"ref44","first-page":"31292","article-title":"UPop: Unified and progressive pruning for compressing vision-language transformers","volume-title":"Proc. Mach. Learn. Res.","author":"Shi","year":"2023"},{"key":"ref45","article-title":"Data-independent module-aware pruning for hierarchical vision transformers","author":"He","year":"2024"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66709-6_15"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73007-8_6"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2023.10.014"},{"key":"ref49","first-page":"1","article-title":"Visual transformer pruning","volume-title":"Proc. KDD Workshop","author":"Zhu","year":"2021"},{"key":"ref50","article-title":"Vision transformer compression with structured pruning and low rank approximation","author":"Kumar","year":"2022"},{"key":"ref51","article-title":"Automatic channel pruning for multi-head attention","author":"Lee","year":"2024"},{"key":"ref52","article-title":"Efficient vision transformer for human pose estimation via patch selection","volume-title":"Proc. Brit. Mach. Vis. Conf.","author":"Kinfu","year":"2023"},{"key":"ref53","first-page":"1","article-title":"Not all patches are what you need: Expediting vision transformers via token reorganizations","volume-title":"Proc. 10th Int. Conf. Learn. Representations","author":"Liang","year":"2022"},{"key":"ref54","first-page":"13937","article-title":"DynamicViT: Efficient vision transformers with dynamic token sparsification","volume":"34","author":"Rao","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/hpca56546.2023.10071047"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.01185"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/iccv51070.2023.00078"},{"key":"ref58","article-title":"Ppt: Token pruning and pooling for efficient vision transformers","author":"Wu","year":"2023"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52729.2023.00208"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106235"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00264"},{"key":"ref62","first-page":"1","article-title":"Synergistic patch pruning for vision transformer: Unifying intra-& inter-layer patch importance","volume-title":"Proc. 12th Int. Conf. Learn. Representations","author":"Zhang","year":"2024"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00016"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3410231"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00141"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20083-0_37"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00533"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2025.3616854"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/FCCM60383.2024.00018"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2023.3261935"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52729.2023.02333"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26298"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1145\/3505244"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i3.20222"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52729.2023.01779"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-023-10489-1"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/dac56929.2023.10247917"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447982"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-39059-3_8"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-023-06304-1"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1145\/3295500.3356156"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/ijcnn48605.2020.9207588"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/jiot.2017.2711426"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1007\/s10579-023-09687-8"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1066"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/ijcnn.2017.7966185"},{"key":"ref87","first-page":"1","article-title":"Learning sparse neural networks via sensitivity-driven regularization","author":"Tartaglione","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref88","first-page":"1","article-title":"Dynamic sparse training: Find efficient sparse network from scratch with trainable masked layers","volume-title":"Proc. 8th Int. Conf. Learn. Representations","author":"Liu","year":"2020"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/icce-asia49877.2020.9277137"},{"key":"ref90","first-page":"55160","article-title":"Fantastic weights and how to find them: Where to prune in dynamic sparse training","volume":"36","author":"Nowak","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.3024992"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52729.2023.02170"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3165123"},{"key":"ref94","first-page":"1","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","volume-title":"Proc. 4th Int. Conf. Learn. Representations","author":"Han","year":"2016"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/access.2022.3168861"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2018.2878258"},{"key":"ref97","first-page":"10876","article-title":"Deep learning through the lens of example difficulty","volume":"34","author":"Baldock","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref98","first-page":"8080","article-title":"HydraNets: Specialized dynamic architectures for efficient inference","volume-title":"Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit.","author":"Mullapudi","year":"2018"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.01213"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2023.3294805"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.06.015"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2018.09.002"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1080\/10556788.2018.1480625"},{"key":"ref104","first-page":"3438","article-title":"Understanding attention for vision-and-language tasks","volume-title":"Proc.-Int. Conf. Comput. Linguistics","author":"Cao","year":"2022"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-72069-8_2"},{"key":"ref106","article-title":"Neural architecture search: Insights from 1000 papers","author":"White","year":"2023"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1145\/3297001.3297062"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.2200\/S00737ED1V01Y201610AIM033"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.56726\/irjmets49459"},{"key":"ref110","first-page":"17081","article-title":"Contrastive learning with adversarial examples","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ho","year":"2020"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1145\/3745028"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.127449"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2025.131615"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1109\/wacv61041.2025.00197"}],"container-title":["IEEE Open Journal of the Computer Society"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8782664\/11319293\/11532952.pdf?arnumber=11532952","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:58:49Z","timestamp":1780603129000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11532952\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":114,"URL":"https:\/\/doi.org\/10.1109\/ojcs.2026.3692927","relation":{},"ISSN":["2644-1268"],"issn-type":[{"value":"2644-1268","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}