{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:02:36Z","timestamp":1777888956209,"version":"3.51.4"},"reference-count":86,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001666","name":"The National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["624B2119,U21B2037,U22B2051,62176222,62176223,62176226,62072386,62072387,62072389,62002305,62272401"],"award-info":[{"award-number":["624B2119,U21B2037,U22B2051,62176222,62176223,62176226,62072386,62072387,62072389,62002305,62272401"]}],"id":[{"id":"10.13039\/501100001666","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,19]]},"DOI":"10.1109\/iccv51701.2025.01160","type":"proceedings-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:45:49Z","timestamp":1777491949000},"page":"12479-12490","source":"Crossref","is-referenced-by-count":0,"title":["Semantic Alignment and Reinforcement for Data-Free Quantization of Vision Transformers"],"prefix":"10.1109","author":[{"given":"Yunshan","family":"Zhong","sequence":"first","affiliation":[{"name":"Institute of Artificial Intelligence, Xiamen University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuyao","family":"Zhou","sequence":"additional","affiliation":[{"name":"MAC Lab, School of Informatics, Xiamen University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxin","family":"Zhang","sequence":"additional","affiliation":[{"name":"MAC Lab, School of Informatics, Xiamen University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanchen","family":"Sui","sequence":"additional","affiliation":[{"name":"Alibaba Group"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shen","family":"Li","sequence":"additional","affiliation":[{"name":"Alibaba Group"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Li","sequence":"additional","affiliation":[{"name":"Alibaba Group"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Chao","sequence":"additional","affiliation":[{"name":"MAC Lab, School of Informatics, Xiamen University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongrong","family":"Ji","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Xiamen University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00676"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i10.28972"},{"key":"ref3","first-page":"7950","article-title":"Post training 4-bit quantization of convolutional networks for rapiddeployment","author":"Banner","year":"2019","journal-title":"In Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref5","article-title":"Token merging: Your vit but faster","volume-title":"In The Eleventh International Conference on Learning Representations (ICLR)","author":"Bolya"},{"key":"ref6","first-page":"13169","article-title":"Mahoney, and Kurt Keutzer","volume-title":"Zeroq: A novel zero shot quantization framework. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Cai"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/iccv48922.2021.00045"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25860"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01574"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00803"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0014"},{"key":"ref14","first-page":"14835","article-title":"Qimera: Data-free quantization with synthetic boundary supporting samples","author":"Choi","year":"2021","journal-title":"In Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00813"},{"key":"ref16","first-page":"2","article-title":"Mimiq: Lowbit data-free quantization of vision transformers","author":"Choi","year":"2024","journal-title":"arXiv preprint"},{"key":"ref17","article-title":"On the relationship between self-attention and convolutional layers","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Cordonnier"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547826"},{"key":"ref19","first-page":"2793","article-title":"Attention is not all you need: Pure attention loses rank doubly exponentially with depth","volume-title":"In International conference on machine learning (ICML)","author":"Dong"},{"key":"ref20","article-title":"An image is worth 16 \u00d7 16 words: Transformers for image recognition at scale","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Dosovitskiy"},{"key":"ref21","article-title":"Sharpness-aware data generation for zeroshot quantization","volume-title":"In International Conference on Machine Learning (ICML)","author":"Anh Dung"},{"key":"ref22","article-title":"Learned step size quantization","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Esser"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/327"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01557"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00495"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref27","article-title":"Squant: On-the-fly data-free quantization via diagonal hessian approximation","volume-title":"In The Eleventh International Conference on Learning Representations (ICLR)","author":"Guo"},{"key":"ref28","article-title":"Transformer in transformer","author":"Han","year":"2021","journal-title":"In Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3152247"},{"key":"ref30","article-title":"Learning efficient vision transformers via fine-grained manifold distillation","author":"Hao","year":"2021","journal-title":"In Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW60793.2023.00085"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00411"},{"key":"ref33","article-title":"Sparse model inversion: Efficient inversion of vision transformers for data-free applications","volume-title":"In International Conference on Machine Learning (ICML)","author":"Hu"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.1999.786990"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01161"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3505244"},{"key":"ref37","first-page":"11102","article-title":"Dataset condensation via efficient syntheticdata parameterization","volume-title":"In International Conference on Machine Learning (ICML)","author":"Kim"},{"key":"ref38","article-title":"Adam: A method for stochastic optimization","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Kingma"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1806.08342"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02339"},{"key":"ref41","article-title":"Additive powers-oftwo quantization: An efficient non-uniform discretization for neural networks","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Li"},{"key":"ref42","article-title":"Brecq: Pushing the limit of post-training quantization by block reconstruction","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Li"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2496"},{"key":"ref44","article-title":"Stableq: Enhancing data-scarce quantization with text-to-image data","author":"Li","year":"2023","journal-title":"arXiv preprint"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72624-8_13"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01565"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20083-0_10"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3301007"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/iccv51070.2023.01580"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/164"},{"key":"ref52","first-page":"21813","article-title":"Oscillation-free quantization for low-bit vision transformers","volume-title":"In International Conference on Machine Learning (ICML)","author":"Liu"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01946"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref55","first-page":"28092","article-title":"Post-training quantization for vision transformer","author":"Liu","year":"2021","journal-title":"In Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109420"},{"key":"ref57","article-title":"Mobilevit: Lightweight, general-purpose, and mobile-friendly vision transformer","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Mehta"},{"key":"ref58","first-page":"23296","article-title":"Intriguing properties of vision transformers","author":"Muzammal Naseer","year":"2021","journal-title":"In Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00355"},{"key":"ref60","first-page":"8026","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"Paszke","year":"2019","journal-title":"In Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00769"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72855-6_18"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102802"},{"key":"ref65","article-title":"P4q: Learning to prompt for quantization in visual-language models","author":"Sun","year":"2024","journal-title":"arXiv preprint"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00498"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01185"},{"key":"ref68","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"In International Conference on Machine Learning (ICML)","author":"Touvron"},{"key":"ref69","first-page":"2579","article-title":"Visualizing data using t-sne","volume":"9","author":"van der Maaten","year":"2008","journal-title":"Journal of Machine Learning Research (JMLR)"},{"key":"ref70","article-title":"Anti-oversmoothing in deep vision transformers via the fourier domain analysis: From theory to practice","author":"Wang","year":"2022","journal-title":"arXiv preprint"},{"key":"ref71","article-title":"Qdrop: Randomly dropping quantization for extremely low-bit post-training quantization","volume-title":"In International Conference on Learning Representations (ICLR)","author":"Wei"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00988"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19803-8_5"},{"key":"ref74","article-title":"Variation-aware vision transformer quantization","author":"Shen","year":"2023","journal-title":"arXiv preprint"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58610-2_1"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58610-2_1"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00874"},{"key":"ref78","article-title":"Understanding neural networks through deep visualization","author":"Yosinski","year":"2015","journal-title":"arXiv preprint"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01183"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01540"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00614"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00681"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01202"},{"key":"ref85","article-title":"I&s-vit: An inclusive & stable method for pushing the limit of post-training vits quantization","author":"Zhong","year":"2023","journal-title":"arXiv preprint"},{"key":"ref86","article-title":"Erq: Error reduction for post-training quantization of vision transformers","volume-title":"In International Conference on Machine Learning (ICML)","author":"Zhong"}],"event":{"name":"2025 IEEE\/CVF International Conference on Computer Vision (ICCV)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,10,19]]},"end":{"date-parts":[[2025,10,25]]}},"container-title":["2025 IEEE\/CVF International Conference on Computer Vision (ICCV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11443115\/11443287\/11445892.pdf?arnumber=11445892","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:03:36Z","timestamp":1777611816000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11445892\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":86,"URL":"https:\/\/doi.org\/10.1109\/iccv51701.2025.01160","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}