{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T01:25:37Z","timestamp":1777339537253,"version":"3.51.4"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62476110"],"award-info":[{"award-number":["62476110"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2341229"],"award-info":[{"award-number":["U2341229"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NSF","award":["III-2106758"],"award-info":[{"award-number":["III-2106758"]}]},{"name":"NSF","award":["POSE-2346158"],"award-info":[{"award-number":["POSE-2346158"]}]},{"name":"National Key R&D Program of China","award":["2021ZD0112500"],"award-info":[{"award-number":["2021ZD0112500"]}]},{"name":"Key R&D Project of Jilin Province","award":["20240304200SF"],"award-info":[{"award-number":["20240304200SF"]}]},{"name":"International Cooperation Project of Jilin Province","award":["20220402009GH"],"award-info":[{"award-number":["20220402009GH"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1109\/tkde.2025.3591771","type":"journal-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T18:44:59Z","timestamp":1753296299000},"page":"5852-5865","source":"Crossref","is-referenced-by-count":1,"title":["EGNN: Exploring Structure-Level Neighborhoods in Graphs With Varying Homophily Ratios"],"prefix":"10.1109","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6149-3214","authenticated-orcid":false,"given":"Songwei","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence and Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7750-0420","authenticated-orcid":false,"given":"Bo","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0315-3547","authenticated-orcid":false,"given":"Sinuo","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6980-8062","authenticated-orcid":false,"given":"Zhejian","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8658-9447","authenticated-orcid":false,"given":"Jifeng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3491-5968","authenticated-orcid":false,"given":"Philip S.","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7835-9556","authenticated-orcid":false,"given":"Hechang","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Welling"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3176880"},{"key":"ref3","first-page":"28748","article-title":"When do graph neural networks help with node classification? Investigating the homophily principle on node distinguishability","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Luan"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3295367"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583256"},{"key":"ref6","first-page":"8463","article-title":"Certified robustness of graph convolution networks for graph classification under topological attacks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Jin"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3271677"},{"key":"ref8","first-page":"13242","article-title":"Finding global homophily in graph neural networks when meeting heterophily","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li","year":"2022"},{"key":"ref9","first-page":"40078","article-title":"Multi-track message passing: Tackling oversmoothing and oversquashing in graph learning via preventing heterophily mixing","volume-title":"Proc. 41st Int. Conf. Mach. Learn.","author":"Pei"},{"key":"ref10","first-page":"12782","article-title":"$\\rm g^{2}$g2 CN: Graph Gaussian convolution networks with concentrated graph filters","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16514"},{"key":"ref12","article-title":"Revisiting graph neural networks: All we have is low-pass filters","author":"Nt","year":"2019"},{"key":"ref13","article-title":"Geom-GCN: Geometric graph convolutional networks","author":"Pei","year":"2020"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20340"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5354"},{"key":"ref16","first-page":"7793","article-title":"Beyond homophily in graph neural networks: Current limitations and effective designs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhu"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1995.488968"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119095"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008202821328"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2013.12.007"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.cad.2010.12.015"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1126\/science.220.4598.671"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v29i3.2157"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2025.3547817"},{"key":"ref25","first-page":"20887","article-title":"Large scale learning on non-homophilous graphs: New benchmarks and strong simple methods","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lim"},{"key":"ref26","first-page":"20321","article-title":"Node dependent local smoothing for scalable graph learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref27","first-page":"6861","article-title":"Simplifying graph convolutional networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Wu"},{"key":"ref28","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017"},{"key":"ref29","article-title":"Predict then propagate: Graph neural networks meet personalized pagerank","author":"Gasteiger","year":"2018"},{"key":"ref30","first-page":"1725","article-title":"Simple and deep graph convolutional networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen"},{"key":"ref31","first-page":"1025","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hamilton"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s40304-023-00392-0"},{"key":"ref33","article-title":"DropEdge: Towards deep graph convolutional networks on node classification","author":"Rong","year":"2019"},{"key":"ref34","article-title":"DynGEM: Deep embedding method for dynamic graphs","author":"Goyal","year":"2018"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330851"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3300879"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583268"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i12.33461"},{"key":"ref40","article-title":"Adaptive universal generalized pagerank graph neural network","author":"Chien","year":"2020"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20340"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2024\/278"},{"key":"ref43","first-page":"10909","article-title":"Predicting global label relationship matrix for graph neural networks under heterophily","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Liang"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/69\/11163535\/11091505-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/69\/11163535\/11091505.pdf?arnumber=11091505","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T05:42:28Z","timestamp":1757742148000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11091505\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":43,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2025.3591771","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]}}}