{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:14:40Z","timestamp":1761894880256,"version":"build-2065373602"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006180","name":"Technology Development","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006180","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/icme59968.2025.11209061","type":"proceedings-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T17:57:42Z","timestamp":1761847062000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["DEQuant: Distribution-Enhanced Reconstruction for Post-Training Quantization"],"prefix":"10.1109","author":[{"given":"Guoming","family":"Lu","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China (UESTC),The Institute of Intelligent Computing,Chengdu,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guodong","family":"Zou","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China (UESTC),The Institute of Intelligent Computing,Chengdu,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongnan","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China (UESTC),The Institute of Intelligent Computing,Chengdu,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heng","family":"Yin","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China (UESTC),The Institute of Intelligent Computing,Chengdu,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jielei","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China (UESTC),The Institute of Intelligent Computing,Chengdu,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangchun","family":"Luo","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China (UESTC),The Institute of Intelligent Computing,Chengdu,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","year":"2015","author":"Han","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.298"},{"key":"ref3","article-title":"Learning both weights and connections for efficient neural network","volume":"28","author":"Han","year":"2015","journal-title":"Advances in neural information processing systems"},{"article-title":"Pruning filters for efficient convnets","year":"2016","author":"Li","key":"ref4"},{"article-title":"Distilling the knowledge in a neural network","year":"2015","author":"Hinton","key":"ref5"},{"article-title":"Fitnets: Hints for thin deep nets","year":"2014","author":"Romero","key":"ref6"},{"article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","year":"2016","author":"Zagoruyko","key":"ref7"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49660.2025.10889695"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"article-title":"A white paper on neural network quantization","year":"2021","author":"Nagel","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1201\/9781003162810-13"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00972"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298681"},{"key":"ref14","article-title":"Tensorizing neural networks","volume":"28","author":"Novikov","year":"2015","journal-title":"Advances in neural information processing systems"},{"article-title":"Pact: Parameterized clipping activation for quantized neural networks","year":"2018","author":"Choi","key":"ref15"},{"article-title":"Learned step size quantization","year":"2019","author":"Esser","key":"ref16"},{"key":"ref17","first-page":"16318","article-title":"Overcoming oscillations in quantization-aware training","volume-title":"International Conference on Machine Learning","author":"Nagel"},{"article-title":"Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients","year":"2016","author":"Zhou","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00495"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26354"},{"key":"ref21","first-page":"4486","article-title":"Same, same but different: Recovering neural network quantization error through weight factorization","volume-title":"International Conference on Machine Learning","author":"Meller"},{"key":"ref22","first-page":"7543","article-title":"Improving neural network quantization without retraining using outlier channel splitting","volume-title":"International conference on machine learning","author":"Zhao"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00363"},{"key":"ref24","article-title":"Post training 4-bit quantization of convolutional networks for rapid-deployment","volume":"32","author":"Banner","year":"2019","journal-title":"Advances in Neural Information Processing Systems"},{"article-title":"Improving post training neural quantization: Layer-wise calibration and integer programming","year":"2020","author":"Hubara","key":"ref25"},{"key":"ref26","first-page":"7197","article-title":"Up or down? adaptive rounding for post-training quantization","volume-title":"International Conference on Machine Learning","author":"Nagel"},{"article-title":"Brecq: Pushing the limit of post-training quantization by block reconstruction","year":"2021","author":"Li","key":"ref27"},{"article-title":"Qdrop: Randomly dropping quantization for extremely low-bit post-training quantization","year":"2022","author":"Wei","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02340"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00768"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00145"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01044"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"}],"event":{"name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","start":{"date-parts":[[2025,6,30]]},"location":"Nantes, France","end":{"date-parts":[[2025,7,4]]}},"container-title":["2025 IEEE International Conference on Multimedia and Expo (ICME)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11208895\/11208897\/11209061.pdf?arnumber=11209061","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T05:37:59Z","timestamp":1761889079000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11209061\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/icme59968.2025.11209061","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}