{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T12:42:07Z","timestamp":1776775327441,"version":"3.51.2"},"reference-count":41,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["202406470057"],"award-info":[{"award-number":["202406470057"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002766","name":"Beijing University of Posts and Telecommunications","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002766","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U22B2019"],"award-info":[{"award-number":["U22B2019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.neucom.2026.133500","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:54:45Z","timestamp":1774630485000},"page":"133500","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Addressing graph heterogeneity and heterophily from a spectral perspective"],"prefix":"10.1016","volume":"683","author":[{"given":"Kangkang","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanhua","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruopei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nan","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1931-7775","authenticated-orcid":false,"given":"Zhiyong","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunshan","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meiyu","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuling","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiting","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yimeng","family":"Ren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tat-Seng","family":"Chua","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.133500_bib0005","series-title":"International Conference on Machine Learning","first-page":"21","article-title":"MixHop: higher-order graph convolutional architectures via sparsified neighborhood mixing","author":"Abu-El-Haija","year":"2019"},{"key":"10.1016\/j.neucom.2026.133500_bib0010","doi-asserted-by":"crossref","first-page":"38436","DOI":"10.52202\/068431-2785","article-title":"Descent steps of a relation-aware energy produce heterogeneous graph neural networks","volume":"35","author":"Ahn","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133500_bib0015","author":"Bo"},{"key":"10.1016\/j.neucom.2026.133500_bib0020","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"3950","article-title":"Beyond low-frequency information in graph convolutional networks","volume":"vol. 35","author":"Bo","year":"2021"},{"key":"10.1016\/j.neucom.2026.133500_bib0025","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1109\/TSP.2023.3259144","article-title":"Convolutional learning on multigraphs","volume":"71","author":"Butler","year":"2023","journal-title":"IEEE Trans. Signal Process."},{"key":"10.1016\/j.neucom.2026.133500_bib0030","series-title":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","first-page":"307","article-title":"Large language model-driven meta-structure discovery in heterogeneous information network","author":"Chen","year":"2024"},{"key":"10.1016\/j.neucom.2026.133500_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106965","article-title":"Heterogeneous graph embedding with dual edge differentiation","volume":"183","author":"Chen","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.neucom.2026.133500_bib0040","first-page":"1","article-title":"Bridging the gap between spatial and spectral domains: a unified framework for graph neural networks","volume":"56","author":"Chen","year":"2023","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.neucom.2026.133500_bib0045","series-title":"International Conference on Learning Representations","article-title":"Adaptive universal generalized pagerank graph neural network","author":"Chien","year":"2021"},{"key":"10.1016\/j.neucom.2026.133500_bib0050","series-title":"Proceedings of the 30th International Conference on Neural Information Processing Systems","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","volume":"vol. 29","author":"Defferrard","year":"2016"},{"key":"10.1016\/j.neucom.2026.133500_bib0055","series-title":"The World Wide Web Conference","first-page":"2331","article-title":"MAGNN: metapath aggregated graph neural network for heterogeneous graph embedding","author":"Fu","year":"2020"},{"key":"10.1016\/j.neucom.2026.133500_bib0060","series-title":"International Conference on Learning Representations","article-title":"Predict then propagate: graph neural networks meet personalized pagerank","author":"Gasteiger","year":"2019"},{"key":"10.1016\/j.neucom.2026.133500_bib0065","series-title":"Proceedings of the ACM Web Conference 2023","first-page":"511","article-title":"Homophily-oriented heterogeneous graph rewiring","author":"Guo","year":"2023"},{"key":"10.1016\/j.neucom.2026.133500_bib0070","series-title":"Proceedings of the ACM on Web Conference 2024","first-page":"685","article-title":"Spectral heterogeneous graph convolutions via positive noncommutative polynomials","author":"He","year":"2024"},{"key":"10.1016\/j.neucom.2026.133500_bib0075","doi-asserted-by":"crossref","first-page":"7264","DOI":"10.52202\/068431-0527","article-title":"Convolutional neural networks on graphs with chebyshev approximation, revisited","volume":"35","author":"He","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133500_bib0080","first-page":"14239","article-title":"BernNet: learning arbitrary graph spectral filters via Bernstein approximation","volume":"34","author":"He","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133500_bib0085","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"11835","article-title":"Multiplex graph representation learning with homophily and consistency","volume":"vol. 39","author":"Huang","year":"2025"},{"key":"10.1016\/j.neucom.2026.133500_bib0090","series-title":"International Conference on Learning Representations","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2017"},{"key":"10.1016\/j.neucom.2026.133500_bib0095","first-page":"44240","article-title":"Long-range meta-path search on large-scale heterogeneous graphs","volume":"37","author":"Li","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133500_bib0100","doi-asserted-by":"crossref","first-page":"7852","DOI":"10.1109\/TPAMI.2025.3573615","article-title":"Heterophily-aware representation learning on heterogeneous graphs","volume":"47","author":"Li","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133500_bib0105","series-title":"ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"7760","article-title":"Spectral graph neural networks with generalized laguerre approximation","author":"Li","year":"2024"},{"key":"10.1016\/j.neucom.2026.133500_bib0110","series-title":"2024 IEEE 40th International Conference on Data Engineering (ICDE)","first-page":"2779","article-title":"HGAMLP: heterogeneous graph attention MLP with de-redundancy mechanism","author":"Liang","year":"2024"},{"key":"10.1016\/j.neucom.2026.133500_bib0115","author":"Liao"},{"key":"10.1016\/j.neucom.2026.133500_bib0120","series-title":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","first-page":"5607","article-title":"When heterophily meets heterogeneity: challenges and a new large-scale graph benchmark","author":"Lin","year":"2025"},{"key":"10.1016\/j.neucom.2026.133500_bib0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2023.103600","article-title":"Towards human-like perception: learning structural causal model in heterogeneous graph","volume":"61","author":"Lin","year":"2024","journal-title":"Inf. Process. Manag."},{"key":"10.1016\/j.neucom.2026.133500_bib0130","article-title":"EvoPath: evolutionary meta-path discovery with large language models for complex heterogeneous information networks","volume":"62","author":"Liu","year":"2025","journal-title":"Inf. Process. Manag."},{"key":"10.1016\/j.neucom.2026.133500_bib0135","series-title":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","first-page":"1150","article-title":"Are we really making much progress? Revisiting, benchmarking and refining heterogeneous graph neural networks","author":"Lv","year":"2021"},{"key":"10.1016\/j.neucom.2026.133500_bib0140","series-title":"International Conference on Learning Representations","article-title":"Geom-GCN: geometric graph convolutional networks","author":"Pei","year":"2020"},{"key":"10.1016\/j.neucom.2026.133500_bib0145","series-title":"European Semantic Web Conference","first-page":"593","article-title":"Modeling relational data with graph convolutional networks","author":"Schlichtkrull","year":"2018"},{"key":"10.1016\/j.neucom.2026.133500_bib0150","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1109\/TKDE.2018.2833443","article-title":"Heterogeneous information network embedding for recommendation","volume":"31","author":"Shi","year":"2018","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.neucom.2026.133500_bib0155","series-title":"Mining Heterogeneous Information Networks: Principles and Methodologies","author":"Sun","year":"2012"},{"key":"10.1016\/j.neucom.2026.133500_bib0160","series-title":"International Conference on Learning Representations","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2019"},{"key":"10.1016\/j.neucom.2026.133500_bib0165","series-title":"The World Wide Web Conference","first-page":"2022","article-title":"Heterogeneous graph attention network","author":"Wang","year":"2019"},{"key":"10.1016\/j.neucom.2026.133500_bib0170","series-title":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","first-page":"1726","article-title":"Self-supervised heterogeneous graph neural network with co-contrastive learning","author":"Wang","year":"2021"},{"key":"10.1016\/j.neucom.2026.133500_bib0175","series-title":"International Conference on Machine Learning","first-page":"23341","article-title":"How powerful are spectral graph neural networks","author":"Wang","year":"2022"},{"key":"10.1016\/j.neucom.2026.133500_bib0180","series-title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","first-page":"2298","article-title":"Ensemble multi-relational graph neural networks","author":"Wang","year":"2022"},{"key":"10.1016\/j.neucom.2026.133500_bib0185","series-title":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","first-page":"2692","article-title":"Shape-aware graph spectral learning","author":"Xu","year":"2024"},{"key":"10.1016\/j.neucom.2026.133500_bib0190","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"10816","article-title":"Simple and efficient heterogeneous graph neural network","volume":"vol. 37","author":"Yang","year":"2023"},{"key":"10.1016\/j.neucom.2026.133500_bib0195","series-title":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","first-page":"2377","article-title":"Multiplex heterogeneous graph convolutional network","author":"Yu","year":"2022"},{"key":"10.1016\/j.neucom.2026.133500_bib0200","first-page":"32","article-title":"Graph transformer networks","author":"Yun","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133500_bib0205","first-page":"7793","article-title":"Beyond homophily in graph neural networks: current limitations and effective designs","volume":"33","author":"Zhu","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226008970?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226008970?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T11:48:16Z","timestamp":1776772096000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226008970"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":41,"alternative-id":["S0925231226008970"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133500","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Addressing graph heterogeneity and heterophily from a spectral perspective","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133500","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"133500"}}