{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T16:10:33Z","timestamp":1781799033895,"version":"3.54.5"},"reference-count":79,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Natural Science Foundation of Chongqing, China","award":["CSTB2023NSCQ-MSX0881"],"award-info":[{"award-number":["CSTB2023NSCQ-MSX0881"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["SWU-KR22032"],"award-info":[{"award-number":["SWU-KR22032"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Visual. Comput. Graphics"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1109\/tvcg.2024.3456141","type":"journal-article","created":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T19:06:21Z","timestamp":1725995181000},"page":"1257-1267","source":"Crossref","is-referenced-by-count":4,"title":["Graph Transformer for Label Placement"],"prefix":"10.1109","volume":"31","author":[{"given":"Jingwei","family":"Qu","sequence":"first","affiliation":[{"name":"College of Computer and Information Science, Southwest University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pingshun","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Computer and Information Science, Southwest University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enyu","family":"Che","sequence":"additional","affiliation":[{"name":"College of Computer and Information Science, Southwest University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinan","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Computer and Information Science, Southwest University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4094-8413","authenticated-orcid":false,"given":"Haibin","family":"Ling","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Stony Brook University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"21","article-title":"MixHop: Higher-order graph convolutional architectures via sparsified neighborhood mixing","volume-title":"Proc. of ICML","author":"Abu-El-Haija"},{"issue":"1","key":"ref2","first-page":"1","article-title":"Label layout for interactive 3d illustrations","volume":"13","author":"Ali","year":"2005","journal-title":"Journal of World Society for Computer Graphics"},{"key":"ref3","article-title":"Relational inductive biases, deep learning, and graph networks","volume":"abs\/1806.01261","author":"Battaglia","year":"2018","journal-title":"CoRR"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-009-9283-6"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.13729"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2023.3313729"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1147\/sj.41.0025"},{"key":"ref8","article-title":"How attentive are graph attention networks?","volume-title":"Proc. of ICLR","author":"Brody","year":"2022"},{"key":"ref9","first-page":"4869","article-title":"Hyperbolic graph convolutional neural networks","volume-title":"Proc. of NeurIPS","author":"Chami"},{"key":"ref10","first-page":"1725","article-title":"Simple and deep graph convolutional networks","volume-title":"Proc. of ICML","author":"Chen"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2023.3326568"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/212332.212334"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2018.2833479"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2020.3027368"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1606.09375"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref17","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. of NAACL","author":"Devlin"},{"key":"ref18","article-title":"Relational Attention: Generalizing transformers for graph-structured tasks","volume-title":"Proc. of ICLR","author":"Diao","year":"2023"},{"key":"ref19","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","volume-title":"Proc. of ICLR","author":"Dosovitskiy","year":"2021"},{"key":"ref20","article-title":"Fast graph representation learning with PyTorch Geometric","volume-title":"Proc. of ICLR","author":"Fey","year":"2019"},{"key":"ref21","first-page":"1263","article-title":"Neural message passing for quantum chemistry","volume-title":"Proc. of ICML","author":"Gilmer"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISMAR.2012.6402555"},{"key":"ref23","article-title":"Anti-Symmetric DGN: a stable architecture for Deep Graph Networks","volume-title":"Proc. of ICLR","author":"Gravina","year":"2023"},{"key":"ref24","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. of NeurIPS","author":"Hamilton"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093587"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-020-01939-w"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-015-0028-4"},{"key":"ref30","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. of ICLR","author":"Kingma","year":"2015"},{"key":"ref31","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. of ICLR","author":"Kipf","year":"2017"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2018.2864491"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2020.2975583"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2018.2854737"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2023.3327398"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICME57554.2024.10687853"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2022.3209353"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3133511"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403076"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2008.152"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/PACIFICVIS.2015.7156379"},{"key":"ref43","first-page":"4602","article-title":"Higher-order graph neural networks","volume-title":"Proc. of AAAI","author":"Morris"},{"key":"ref44","first-page":"87","article-title":"HoloBee: Augmented reality based bee drift analysis","volume-title":"Proc. of ISMAR","author":"Nguyen"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/2678025.2701375"},{"key":"ref46","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume-title":"Proc. of NeurIPS","author":"Paszke"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3114854"},{"key":"ref48","article-title":"A practical guide and software for analysing pairwise comparison experiments","volume":"abs\/1712.03686","author":"P\u00e9rez-Ortiz","year":"2017","journal-title":"CoRR"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/3491102.3502026"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/134"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/bibm52615.2021.9669683"},{"key":"ref52","first-page":"14501","article-title":"Recipe for a general, powerful, scalable graph transformer","volume-title":"Proc. of NeurIPS","author":"Ramp\u00e1\u0161ek"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2016.2577031"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2017.12"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/214"},{"key":"ref56","article-title":"Adaptive filters and aggregator fusion for efficient graph convolutions","volume":"abs\/2104.01481","author":"Tailor","year":"2021","journal-title":"CoRR"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/VR.2014.6802046"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/VR.2013.6549347"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/VR.2016.7504691"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/VR55154.2023.00054"},{"key":"ref61","article-title":"How to analyze paired comparison data","volume-title":"UWEE Technical Report 206","author":"Tsukida","year":"2011"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref63","article-title":"Graph attention networks","volume-title":"Proc. of ICLR","author":"Veli\u010dkovi\u0107","year":"2018"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00759"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2629340"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ISMAR55827.2022.00060"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2022.3209475"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2022.3141585"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref70","article-title":"Capsule graph neural network","volume-title":"Proc. of ICLR","author":"Xinyi","year":"2019"},{"key":"ref71","first-page":"10524","article-title":"On layer normalization in the transformer architecture","volume-title":"Proc. of ICML","author":"Xiong"},{"key":"ref72","article-title":"How powerful are graph neural networks?","volume-title":"Proc. of ICLR","author":"Xu","year":"2019"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1145\/3379337.3415819"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.261"},{"key":"ref75","first-page":"28877","article-title":"Do transformers really perform badly for graph representation?","volume-title":"Proc. of NeurIPS","author":"Ying"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1179\/caj.1972.9.2.99"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3204236"},{"key":"ref78","article-title":"Rethinking the expressive power of gnns via graph biconnectivity","author":"Zhang","year":"2023","journal-title":"Proc. of ICLR"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3106492"}],"container-title":["IEEE Transactions on Visualization and Computer Graphics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/2945\/10766346\/10670468.pdf?arnumber=10670468","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:36:13Z","timestamp":1732667773000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10670468\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":79,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tvcg.2024.3456141","relation":{},"ISSN":["1077-2626","1941-0506","2160-9306"],"issn-type":[{"value":"1077-2626","type":"print"},{"value":"1941-0506","type":"electronic"},{"value":"2160-9306","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]}}}