{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T07:32:12Z","timestamp":1767598332912,"version":"3.37.3"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2020YFB1804604"],"award-info":[{"award-number":["2020YFB1804604"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076130","91846104"],"award-info":[{"award-number":["62076130","91846104"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Industry and Information Technology of China"},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Fund for the Central Universities","doi-asserted-by":"crossref","award":["30918012204","30920041112"],"award-info":[{"award-number":["30918012204","30920041112"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1109\/tpami.2023.3338216","type":"journal-article","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T18:28:09Z","timestamp":1701455289000},"page":"3169-3182","source":"Crossref","is-referenced-by-count":5,"title":["A Little Truth Injection But a Big Reward: Label Aggregation With Graph Neural Networks"],"prefix":"10.1109","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1881-585X","authenticated-orcid":false,"given":"Zijian","family":"Ying","sequence":"first","affiliation":[{"name":"School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2541-4923","authenticated-orcid":false,"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Nanjing University of Science and Technology, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0998-1517","authenticated-orcid":false,"given":"Qianmu","family":"Li","sequence":"additional","affiliation":[{"name":"Digital Economy Research Institute, Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4556-1437","authenticated-orcid":false,"given":"Ming","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Automation, Hohai University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4960-174X","authenticated-orcid":false,"given":"Victor S.","family":"Sheng","sequence":"additional","affiliation":[{"name":"Texas Tech University, Lubbock, TX, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528120"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3148148"},{"key":"ref3","first-page":"82","article-title":"Learning to predict from crowdsourced data","volume-title":"Proc. 13th Conf. Uncertainty Artif. Intell.","author":"Bi"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/210"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.2307\/2346806"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2187836.2187900"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-023-00624-6"},{"key":"ref8","first-page":"242","article-title":"Training deep neural nets to aggregate crowdsourced responses","volume-title":"Proc. 32nd Conf. Uncertainty Artif. Intell.","author":"Gaunt"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/238"},{"key":"ref10","first-page":"1263","article-title":"Neural message passing for quantum chemistry","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gilmer"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2005.1555942"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.01.008"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00378"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-013-0306-1"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_17"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v35i2.2537"},{"article-title":"Quality control of crowd labeling through expert evaluation","volume-title":"Proc. NIPS 2nd Workshop Comput. Social Sci. Wisdom Crowds","author":"Khattak","key":"ref17"},{"key":"ref18","first-page":"619","article-title":"Bayesian classifier combination","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Kim"},{"key":"ref19","first-page":"1","article-title":"Semi-supervised classification with graph convolution networks","volume-title":"Proc. Int. Conf. Learn. Representation","author":"Kipf"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2327026"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01421-6_57"},{"key":"ref22","first-page":"3886","article-title":"Exploiting worker correlation for label aggregation in crowdsourcing","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1006\/inco.1994.1009"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.05.060"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/324"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/184"},{"issue":"Apr","key":"ref27","first-page":"1297","article-title":"Learning from crowds","volume":"11","author":"Raykar","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2013.05.012"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11506"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2013.05.012"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33019837"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/hcomp.v1i1.13088"},{"article-title":"Graph attention networks","year":"2017","author":"Veli\u010dkovi\u0107","key":"ref33"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/2566486.2567989"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/hcomp.v3i1.13256"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/413"},{"key":"ref37","first-page":"2424","article-title":"The multidimensional wisdom of crowds","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Welinder"},{"key":"ref38","first-page":"2035","article-title":"Whose vote should count more: Optimal integration of labels from labelers of unknown expertise","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Whitehill"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3556545"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3460865"},{"article-title":"How powerful are graph neural networks?","year":"2018","author":"Xu","key":"ref41"},{"key":"ref42","first-page":"5453","article-title":"Representation learning on graphs with jumping knowledge networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xu"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080679"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2504974"},{"key":"ref45","first-page":"157","article-title":"Leveraging instance features for label aggregation in programmatic weak supervision","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Zhang"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.14778\/3055540.3055547"},{"key":"ref47","first-page":"2195","article-title":"Learning from the wisdom of crowds by minimax entropy","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Zhou"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10490207\/10337741.pdf?arnumber=10337741","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,9]],"date-time":"2024-04-09T19:37:18Z","timestamp":1712691438000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10337741\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5]]},"references-count":47,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2023.3338216","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"type":"print","value":"0162-8828"},{"type":"electronic","value":"2160-9292"},{"type":"electronic","value":"1939-3539"}],"subject":[],"published":{"date-parts":[[2024,5]]}}}