{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T15:53:10Z","timestamp":1781625190642,"version":"3.54.5"},"reference-count":76,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"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-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62471403"],"award-info":[{"award-number":["62471403"]}],"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":["62271411"],"award-info":[{"award-number":["62271411"]}],"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":["U22B2036"],"award-info":[{"award-number":["U22B2036"]}],"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":["U22A2098"],"award-info":[{"award-number":["U22A2098"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Technological Innovation Team of Shaanxi Province","award":["2025RS-CXTD-009"],"award-info":[{"award-number":["2025RS-CXTD-009"]}]},{"name":"International Cooperation Project of Shaanxi Province","award":["2025GH-YBXM-017"],"award-info":[{"award-number":["2025GH-YBXM-017"]}]},{"name":"German Federal Ministry for Economic Affairs and Climate Action","award":["03EI1092A"],"award-info":[{"award-number":["03EI1092A"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1109\/tkde.2026.3677544","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T19:58:07Z","timestamp":1774468687000},"page":"3778-3791","source":"Crossref","is-referenced-by-count":1,"title":["Noise-Filtering Enhanced Graph Transformer for Robust Fake News Detection"],"prefix":"10.1109","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1460-4409","authenticated-orcid":false,"given":"Junyou","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5865-2285","authenticated-orcid":false,"given":"Chao","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-6497-6962","authenticated-orcid":false,"given":"Ze","family":"Yin","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0253-3882","authenticated-orcid":false,"given":"Xianghua","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8182-2852","authenticated-orcid":false,"given":"Zhen","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5926-4276","authenticated-orcid":false,"given":"J\u00fcrgen","family":"Kurths","sequence":"additional","affiliation":[{"name":"Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3185151"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3137597.3137600"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290994"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2021.3130321"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3395046"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1089\/big.2020.0062"},{"key":"ref7","first-page":"281","article-title":"Learning the k in k-means","volume-title":"Proc. Adv. Neural Inf. Process. Syst","author":"Hamerly","year":"2003"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462990"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570478"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3496701"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511999"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5393"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.297"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00037"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20335"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1282"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1002"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.387"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref20","first-page":"28877","article-title":"Do transformers really perform badly for graph representation?","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ying","year":"2021"},{"key":"ref21","first-page":"14501","article-title":"Recipe for a general, powerful, scalable graph transformer","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ramp\u00e1sek","year":"2022"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3672024"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462871"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5386"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.165"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450111"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512122"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3477977"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403092"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16080"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512135"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3390431"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2025.3528951"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511968"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3280555"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2025.3529707"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i1.27757"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511999"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.111715"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.126984"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512163"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3341640"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671977"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2024.3519657"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482481"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00010"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3112497"},{"key":"ref48","article-title":"Transformer for graphs: An overview from architecture perspective","author":"Min","year":"2022"},{"key":"ref49","first-page":"3469","article-title":"Structure-aware transformer for graph representation learning","volume-title":"Proc. 39th Int. Conf. Mach. Learn.","volume":"162","author":"Chen","year":"2022"},{"key":"ref50","first-page":"23321","article-title":"Graph inductive biases in transformers without message passing","volume-title":"Proc. 40th Int. Conf. Mach. Learn.","volume":"202","author":"Ma","year":"2023"},{"key":"ref51","first-page":"21618","article-title":"Rethinking graph transformers with spectral attention","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Kreuzer","year":"2021"},{"key":"ref52","first-page":"4465","article-title":"Distance encoding: Design provably more powerful neural networks for graph representation learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li","year":"2020"},{"key":"ref53","article-title":"Graph neural networks with learnable structural and positional representations","volume-title":"Proc. 10th Int. Conf. Learn. Representations","author":"Dwivedi","year":"2022"},{"key":"ref54","first-page":"12559","article-title":"Self-supervised graph transformer on large-scale molecular data","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Rong","year":"2020"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532031"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref57","first-page":"882","article-title":"Learning to explain: An information-theoretic perspective on model interpretation","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","volume":"80","author":"Chen","year":"2018"},{"key":"ref58","first-page":"79815","article-title":"SDMG: Smoothing your diffusion models for powerful graph representation learning","volume-title":"Proc. 42nd Int. Conf. Mach. Learn.","volume":"267","author":"Zhu","year":"2025"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ASONAM.2018.8508729"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbi.2018.09.009"},{"key":"ref61","first-page":"20437","article-title":"Graph information bottleneck","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wu","year":"2020"},{"key":"ref62","article-title":"Graph information bottleneck for subgraph recognition","volume-title":"Proc. 9th Int. Conf. Learn. Representations","author":"Yu","year":"2021"},{"key":"ref63","article-title":"Categorical reparameterization with gumbel-softmax","volume-title":"Proc. 5th Int. Conf. Learn. Representations","author":"Jang","year":"2017"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00155"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1038\/2041118a0"},{"key":"ref66","article-title":"Information-theoretic analysis of generalization capability of learning algorithms","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Xu","year":"2017"},{"key":"ref67","first-page":"69","article-title":"Classification of an imbalanced data set using decision tree algorithms","volume":"79","author":"Truica","year":"2017","journal-title":"Univ. Politech. Bucharest Sci. Bull. Ser. C Electr. Eng. Comput. Sci"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132877"},{"issue":"1","key":"ref69","first-page":"411","article-title":"spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing","volume":"7","author":"Honnibal","year":"2017","journal-title":"to appear"},{"key":"ref70","first-page":"2769","article-title":"A unified propagation forest-based framework for fake news detection","volume-title":"Proc. 29th Int. Conf. Comput. Linguistics","author":"Wei","year":"2022"},{"key":"ref71","article-title":"GLM-130b: An open bilingual pre-trained model","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Zeng","year":"2023"},{"key":"ref72","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. 5th Int. Conf. Learn. Representations","author":"Kipf","year":"2017"},{"key":"ref73","article-title":"Graph attention networks","volume-title":"Proc. 6th Int. Conf. Learn. Representations","author":"Velickovic","year":"2018"},{"key":"ref74","first-page":"15524","article-title":"Interpretable and generalizable graph learning via stochastic attention mechanism","volume-title":"Proc. 39th Int. Conf. Mach. Learn.","volume":"162","author":"Miao","year":"2022"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i1.27788"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539277"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/69\/11503382\/11455959.pdf?arnumber=11455959","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T19:37:49Z","timestamp":1777923469000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11455959\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":76,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2026.3677544","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":[[2026,6]]}}}