{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T02:45:05Z","timestamp":1783737905228,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3774904.3792482","type":"proceedings-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T12:38:33Z","timestamp":1777293513000},"page":"1183-1194","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["AC$\n                    <sup>2<\/sup>\n                    $L-GAD: Active Counterfactual Contrastive Learning for Graph Anomaly Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4459-0703","authenticated-orcid":false,"given":"Kamal","family":"Berahmand","sequence":"first","affiliation":[{"name":"RMIT University, Melbourne, VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5952-156X","authenticated-orcid":false,"given":"Saman","family":"Forouzandeh","sequence":"additional","affiliation":[{"name":"RMIT University, Melbourne, VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9596-7414","authenticated-orcid":false,"given":"Mehrnoush","family":"Mohammadi","sequence":"additional","affiliation":[{"name":"The University of Queensland, Brisbane, QLD, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5604-565X","authenticated-orcid":false,"given":"Parham","family":"Moradi","sequence":"additional","affiliation":[{"name":"RMIT University, Melbourne, VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0517-9420","authenticated-orcid":false,"given":"Mahdi","family":"Jalili","sequence":"additional","affiliation":[{"name":"RMIT University, Melbourne, VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335388"},{"key":"e_1_3_2_1_2_1","volume-title":"Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI). 1643-1649","author":"Cai Hongyun","year":"2017","unstructured":"Hongyun Cai, Vincent W. Zheng, and Kevin Chen-Chuan Chang. 2017. Active learning for graph-structured data. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI). 1643-1649."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611975673.67"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3575637.3575646"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3696410.3714615"},{"key":"e_1_3_2_1_6_1","first-page":"4362","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"37","author":"Duan Defu","year":"2023","unstructured":"Defu Duan, Zhiqiang Xu, Yanjie Li, and Liang Sun. 2023. Contrastive anomaly detection with graph neural networks (CARD). In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37. AAAI, 4362-4370."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25907"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9054430"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/296"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28691"},{"key":"e_1_3_2_1_11_1","volume-title":"Higher-order Enhanced Contrastive-based Graph Anomaly Detection Without Graph Augmentation. Pattern Recognition","author":"Hu Jingtao","year":"2025","unstructured":"Jingtao Hu, Siwei Wang, Jingcan Duan, Hu Jin, Xinwang Liu, and En Zhu. 2025. Higher-order Enhanced Contrastive-based Graph Anomaly Detection Without Graph Augmentation. Pattern Recognition (2025), 111666."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482057"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3414326"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/299"},{"key":"e_1_3_2_1_15_1","volume-title":"Diffgad: A diffusion-based unsupervised graph anomaly detector. arXiv preprint arXiv:2410.06549","author":"Li Jinghan","year":"2024","unstructured":"Jinghan Li, Yuan Gao, Jinda Lu, Junfeng Fang, CongcongWen, Hui Lin, and Xiang Wang. 2024. Diffgad: A diffusion-based unsupervised graph anomaly detector. arXiv preprint arXiv:2410.06549 (2024)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3679200","article-title":"RevGNN: Negative sampling enhanced contrastive graph learning for academic reviewer recommendation","volume":"43","author":"Liao Weibin","year":"2024","unstructured":"Weibin Liao, Yifan Zhu, Yanyan Li, Qi Zhang, Zhonghong Ou, and Xuesong Li. 2024. RevGNN: Negative sampling enhanced contrastive graph learning for academic reviewer recommendation. ACM Transactions on Information Systems 43, 1 (2024), 1-26.","journal-title":"ACM Transactions on Information Systems"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3068344"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i18.34101"},{"key":"e_1_3_2_1_19_1","first-page":"7103","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"36","author":"Lucic Ana","year":"2022","unstructured":"Ana Lucic, Caner Og' uz, Hinda Haned, and Fabrizio Silvestri. 2022. CFGNN Explainer: Counterfactual Explanations for Graph Neural Networks. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 36. 7103-7111."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498389"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/488"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3015098"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.24"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","first-page":"49490","DOI":"10.52202\/075280-2154","article-title":"Truncated affinity maximization: One class homophily modeling for graph anomaly detection","volume":"36","author":"Qiao Hezhe","year":"2023","unstructured":"Hezhe Qiao and Guansong Pang. 2023. Truncated affinity maximization: One class homophily modeling for graph anomaly detection. Advances in Neural Information Processing Systems 36 (2023), 49490-49512.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_25_1","volume-title":"Deep graph anomaly detection: A survey and new perspectives","author":"Qiao Hezhe","year":"2025","unstructured":"Hezhe Qiao, Hanghang Tong, Bo An, Irwin King, Charu Aggarwal, and Guansong Pang. 2025. Deep graph anomaly detection: A survey and new perspectives. IEEE Transactions on Knowledge and Data Engineering (2025)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3616855.3635767"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1289"},{"key":"e_1_3_2_1_28_1","volume-title":"Proc. 33rd Int. Joint Conf. Artif. Intell. 4955-4963","author":"Tang Liaoyuan","year":"2024","unstructured":"Liaoyuan Tang, Zheng Wang, Guanxiong He, Rong Wang, and Feiping Nie. 2024. Perturbation guiding contrastive representation learning for time series anomaly detection. In Proc. 33rd Int. Joint Conf. Artif. Intell. 4955-4963."},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings of the Web Conference (WWW). 1119-1129","author":"Vu Minh","unstructured":"Minh Vu and My T. Thai. 2022. Counterfactual Graphs for Explainable Graph Neural Networks. In Proceedings of the Web Conference (WWW). 1119-1129."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i20.35458"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512156"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i12.33415"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583499"},{"key":"e_1_3_2_1_34_1","volume-title":"Graph contrastive learning with augmentations. Advances in neural information processing systems 33","author":"You Yuning","year":"2020","unstructured":"Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, and Yang Shen. 2020. Graph contrastive learning with augmentations. Advances in neural information processing systems 33 (2020), 5812-5823."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData52589.2021.9671990"},{"key":"e_1_3_2_1_36_1","first-page":"2376","article-title":"Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks","author":"Zhang Jiaqiang","year":"2022","unstructured":"Jiaqiang Zhang, Senzhang Wang, and Songcan Chen. 2022. Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks. In Proceedings of IJCAI. 2376-2382.","journal-title":"Proceedings of IJCAI."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3696410.3714575"},{"key":"e_1_3_2_1_38_1","volume-title":"Deep Graph Contrastive Representation Learning. In ICML Workshop on Graph Representation Learning.","author":"Zhu Yanqiao","year":"2020","unstructured":"Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, and Liang Wang. 2020. Deep Graph Contrastive Representation Learning. In ICML Workshop on Graph Representation Learning."}],"event":{"name":"WWW '26: The ACM Web Conference 2026","location":"Dubai United Arab Emirates","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2026"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3774904.3792482","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T07:51:22Z","timestamp":1783151482000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774904.3792482"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":38,"alternative-id":["10.1145\/3774904.3792482","10.1145\/3774904"],"URL":"https:\/\/doi.org\/10.1145\/3774904.3792482","relation":{},"subject":[],"published":{"date-parts":[[2026,4,12]]},"assertion":[{"value":"2026-04-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}