{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:05:41Z","timestamp":1754154341436,"version":"3.41.2"},"reference-count":41,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,12,13]],"date-time":"2024-12-13T00:00:00Z","timestamp":1734048000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,13]],"date-time":"2024-12-13T00:00:00Z","timestamp":1734048000000},"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","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,13]]},"DOI":"10.1109\/hpcc64274.2024.00184","type":"proceedings-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T18:33:48Z","timestamp":1753295628000},"page":"1378-1385","source":"Crossref","is-referenced-by-count":0,"title":["UM-Explainer: An Explainability Method for Unsupervised Models Based on Factual and Counterfactual Reasoning"],"prefix":"10.1109","author":[{"given":"Jing","family":"Tan","sequence":"first","affiliation":[{"name":"Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education,Guilin,China,541004"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiyu","family":"Li","sequence":"additional","affiliation":[{"name":"Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linlin","family":"Su","sequence":"additional","affiliation":[{"name":"Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huijiang","family":"Wang","sequence":"additional","affiliation":[{"name":"Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinyan","family":"Wang","sequence":"additional","affiliation":[{"name":"Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education,Guilin,China,541004"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1024","article-title":"Inductive Representation Learning on Large Graphs","author":"Hamilton","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"article-title":"Semi-Supervised Classification with Graph Convolutional Networks","volume-title":"Proceedings of the 5th International Conference on Learning Representations","author":"Kipf","key":"ref2"},{"article-title":"How Powerful are Graph Neural Networks?","volume-title":"Proceedings of the 7th International Conference on Learning Representations","author":"Xu","key":"ref3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.12.112"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20335"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583403"},{"key":"ref7","first-page":"30414","article-title":"Hyperbolic Geometric Latent Diffusion Model for Graph Generation","author":"Fu","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref8","first-page":"30414","article-title":"InfoGCL: Information-Aware Graph Contrastive Learning","author":"Xu","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"article-title":"Deep Graph Infomax","volume-title":"Proceedings of the 7th International Conference on Learning Representations","author":"Velickovic","key":"ref9"},{"key":"ref10","first-page":"4116","article-title":"Contrastive Multi-View Representation Learning on Graphs","volume-title":"Proceedings of the 37th International Conference on Machine Learning","author":"Hassani"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2762"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220001"},{"key":"ref14","article-title":"Task-Agnostic Graph Explanations","author":"Xie","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"article-title":"UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models","volume-title":"Proceedings of the 12th International Conference on Learning Representations","author":"Kang","key":"ref15"},{"key":"ref16","first-page":"4499","article-title":"CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks","volume-title":"Proceedings of the International Conference on Artificial Intelligence and Statistics","author":"Lucic"},{"key":"ref17","first-page":"5644","article-title":"Robust counterfactual explanations on graph neural networks","author":"Bajaj","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511948"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3204236"},{"article-title":"Explainability Techniques for Graph Convolutional Networks","year":"2019","author":"Baldassarre","key":"ref20"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01103"},{"key":"ref22","first-page":"9244","article-title":"Gn-nexplainer: Generating explanations for graph neural networks","author":"Ying","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref23","first-page":"19620","article-title":"Parameterized explainer for graph neural network","author":"Luo","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref24","article-title":"SAME: Uncovering GNN Black Box with Structure-aware Shapley-based Multipiece Explanations","author":"Ye","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref25","article-title":"Gstarx: Explaining graph neural networks with structure-aware cooperative games","author":"Zhang","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357910"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358044"},{"article-title":"Causal screening to interpret graph neural networks","volume-title":"Proceedings of the 9th International Conference Learning Representations","author":"Wang","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3187455"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3461702.3462562"},{"key":"ref31","first-page":"12225","article-title":"Pgm-explainer: Probabilistic graphical model explanations for graph neural networks","author":"Vu","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-5308"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3115452"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403085"},{"article-title":"GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks","volume-title":"Proceedings of the Eleventh International Conference on Learning Representation","author":"Wang","key":"ref35"},{"key":"ref36","first-page":"4391","article-title":"Label-Free Explainability for Unsupervised Models","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Crabbe"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86520-7_19"},{"article-title":"Fast graph representation learning with PyTorch Geometric","year":"2019","author":"Fey","key":"ref38"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1021\/jm00106a046"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-007-0103-5"}],"event":{"name":"2024 IEEE International Conference on High Performance Computing and Communications (HPCC)","start":{"date-parts":[[2024,12,13]]},"location":"Wuhan, China","end":{"date-parts":[[2024,12,15]]}},"container-title":["2024 IEEE International Conference on High Performance Computing and Communications (HPCC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11083115\/11083125\/11083152.pdf?arnumber=11083152","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T04:47:40Z","timestamp":1753332460000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11083152\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,13]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/hpcc64274.2024.00184","relation":{},"subject":[],"published":{"date-parts":[[2024,12,13]]}}}