{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T14:46:52Z","timestamp":1777301212200,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":58,"publisher":"ACM","funder":[{"name":"Hong Kong RGC Theme-based Research Scheme","award":["T41-603\/20-R"],"award-info":[{"award-number":["T41-603\/20-R"]}]},{"name":"The Hong Kong Polytechnic University","award":["Research Institute for Artificial Intelligence of Things"],"award-info":[{"award-number":["Research Institute for Artificial Intelligence of Things"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3774904.3792268","type":"proceedings-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T21:54:34Z","timestamp":1775771674000},"page":"857-868","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["DP-DGAD: A Generalist Dynamic Graph Anomaly Detector with Dynamic Prototypes"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4957-596X","authenticated-orcid":false,"given":"Jialun","family":"Zheng","sequence":"first","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1327-1315","authenticated-orcid":false,"given":"Jie","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, City University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2725-2529","authenticated-orcid":false,"given":"Jiannong","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4444-7811","authenticated-orcid":false,"given":"Xiao","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Software, Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9011-0355","authenticated-orcid":false,"given":"Hanchen","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5741-2047","authenticated-orcid":false,"given":"Yankai","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science, McGill University, Montreal, Canada"}]}],"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\/3459637.3481955"},{"key":"e_1_3_2_1_2_1","first-page":"56310","article-title":"Invariant anomaly detection under distribution shifts: a causal perspective","volume":"36","author":"Carvalho Jo\u00e3o","year":"2023","unstructured":"Jo\u00e3o Carvalho, Mengtao Zhang, Robin Geyer, Carlos Cotrini, and Joachim M Buhmann. 2023. Invariant anomaly detection under distribution shifts: a causal perspective. Advances in Neural Information Processing Systems 36 (2023), 56310-56337.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE60146.2024.00246"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28671"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671747"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3696410.3714591"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498419"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i3.32243"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3136171"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539389"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583402"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583237"},{"key":"e_1_3_2_1_13_1","volume-title":"Causalformer: An interpretable transformer for temporal causal discovery","author":"Kong Lingbai","year":"2024","unstructured":"Lingbai Kong, Wengen Li, Hanchen Yang, Yichao Zhang, Jihong Guan, and Shuigeng Zhou. 2024. Causalformer: An interpretable transformer for temporal causal discovery. IEEE Transactions on Knowledge and Data Engineering (2024)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0033"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671845"},{"key":"e_1_3_2_1_17_1","first-page":"40963","article-title":"Zero-shot anomaly detection via batch normalization","volume":"36","author":"Li Aodong","year":"2023","unstructured":"Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, and Stephan Mandt. 2023. Zero-shot anomaly detection via batch normalization. Advances in Neural Information Processing Systems 36 (2023), 40963-40993.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3696410.3714646"},{"key":"e_1_3_2_1_19_1","volume-title":"DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs. In The Thirty-ninth Annual Conference on Neural Information Processing Systems. https:\/\/openreview.net\/forum?id=ja2wA4UncJ","author":"Li Dongyuan","year":"2025","unstructured":"Dongyuan Li, Shiyin Tan, Ying Zhang, Ming Jin, Shirui Pan, Manabu Okumura, and Renhe Jiang. 2025. DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs. In The Thirty-ninth Annual Conference on Neural Information Processing Systems. https:\/\/openreview.net\/forum?id=ja2wA4UncJ"},{"key":"e_1_3_2_1_20_1","volume-title":"Proceedings of the 38th International Conference on Neural Information Processing Systems. 50772-50804","author":"Liu Yixin","year":"2024","unstructured":"Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, and Shirui Pan. 2024. ARC: a generalist graph anomaly detector with in-context learning. In Proceedings of the 38th International Conference on Neural Information Processing Systems. 50772-50804."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3124061"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3679614"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583386"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671929"},{"key":"e_1_3_2_1_25_1","volume-title":"Zero-shot generalist graph anomaly detection with unified neighborhood prompts. arXiv preprint arXiv:2410.14886","author":"Niu Chaoxi","year":"2024","unstructured":"Chaoxi Niu, Hezhe Qiao, Changlu Chen, Ling Chen, and Guansong Pang. 2024. Zero-shot generalist graph anomaly detection with unified neighborhood prompts. arXiv preprint arXiv:2410.14886 (2024)."},{"key":"e_1_3_2_1_26_1","volume-title":"Clustering in weighted networks. Social networks 31, 2","author":"Opsahl Tore","year":"2009","unstructured":"Tore Opsahl and Pietro Panzarasa. 2009. Clustering in weighted networks. Social networks 31, 2 (2009), 155-163."},{"key":"e_1_3_2_1_27_1","volume-title":"AnomalyGFM: Graph foundation model for zero\/few-shot anomaly detection. arXiv preprint arXiv:2502.09254","author":"Qiao Hezhe","year":"2025","unstructured":"Hezhe Qiao, Chaoxi Niu, Ling Chen, and Guansong Pang. 2025. AnomalyGFM: Graph foundation model for zero\/few-shot anomaly detection. arXiv preprint arXiv:2502.09254 (2025)."},{"key":"e_1_3_2_1_28_1","volume-title":"Forty-second International Conference on Machine Learning.","author":"Qiao Ziyue","year":"2025","unstructured":"Ziyue Qiao, Qianyi Cai, Hao Dong, Jiawei Gu, Pengyang Wang, Meng Xiao, Xiao Luo, and Hui Xiong. 2025. GCAL: Adapting Graph Models to Evolving Domain Shifts. In Forty-second International Conference on Machine Learning."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"e_1_3_2_1_30_1","volume-title":"Program: Prototype graph model based pseudo-label learning for test-time adaptation. In The twelfth international conference on learning representations.","author":"Sun Haopeng","year":"2024","unstructured":"Haopeng Sun, Lumin Xu, Sheng Jin, Ping Luo, Chen Qian, and Wentao Liu. 2024. Program: Prototype graph model based pseudo-label learning for test-time adaptation. In The twelfth international conference on learning representations."},{"key":"e_1_3_2_1_31_1","volume-title":"Sad: Semi-supervised anomaly detection on dynamic graphs. arXiv preprint arXiv:2305.13573","author":"Tian Sheng","year":"2023","unstructured":"Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen, et al. 2023. Sad: Semi-supervised anomaly detection on dynamic graphs. arXiv preprint arXiv:2305.13573 (2023)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3370678"},{"key":"e_1_3_2_1_33_1","volume-title":"Freedyg: Frequency enhanced continuous-time dynamic graph model for link prediction. In The twelfth international conference on learning representations.","author":"Tian Yuxing","year":"2024","unstructured":"Yuxing Tian, Yiyan Qi, and Fan Guo. 2024. Freedyg: Frequency enhanced continuous-time dynamic graph model for link prediction. In The twelfth international conference on learning representations."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i14.29468"},{"key":"e_1_3_2_1_35_1","volume-title":"Victor CM Leung, and Di Wang","author":"Wang Huan","year":"2025","unstructured":"Huan Wang, Junyang Chen, Yirui Wu, Victor CM Leung, and Di Wang. 2025. Epm: Evolutionary perception method for anomaly detection in noisy dynamic graphs. IEEE Transactions on Knowledge and Data Engineering (2025)."},{"key":"e_1_3_2_1_36_1","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 20554-20563","author":"YisenWang HongjunWang","year":"2023","unstructured":"HongjunWang and YisenWang. 2023. Generalist: Decoupling natural and robust generalization. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 20554-20563."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671838"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3726302.3729958"},{"key":"e_1_3_2_1_39_1","volume-title":"Renqiang Luo, Vidya Saikrishna, Shuo Yu, and Xiangjie Kong.","author":"Xia Feng","year":"2025","unstructured":"Feng Xia, Ciyuan Peng, Jing Ren, Falih Gozi Febrinanto, Renqiang Luo, Vidya Saikrishna, Shuo Yu, and Xiangjie Kong. 2025. Graph Learning. Foundations and Trends\u00ae in Signal Processing 19, 4 (2025), 371-551."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.01897"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE55515.2023.00059"},{"key":"e_1_3_2_1_42_1","volume-title":"Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies and Opportunities. ACM Transactions on Knowledge Discovery from Data (July","author":"Yang Hanchen","year":"2025","unstructured":"Hanchen Yang, Jiannong Cao,Wengen Li, ShuyuWang, Hui Li, Jihong Guan, and Shuigeng Zhou. 2025. Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies and Opportunities. ACM Transactions on Knowledge Discovery from Data (July 2025), 1-46."},{"key":"e_1_3_2_1_43_1","volume-title":"UniOcean: A Unified Framework for Predicting Multiple Ocean Factors of Varying Temporal Scales","author":"Yang Hanchen","year":"2024","unstructured":"Hanchen Yang, Yuwei Chen, Jiannong Cao, Wengen Li, Yu Yang, Shuyu Wang, Jihong Guan, Rufu Qin, and Shuigeng Zhou. 2024. UniOcean: A Unified Framework for Predicting Multiple Ocean Factors of Varying Temporal Scales. IEEE Transactions on Geoscience and Remote Sensing (2024)."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2350190.2350193"},{"key":"e_1_3_2_1_45_1","first-page":"22001","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"39","author":"Yang Xiao","year":"2025","unstructured":"Xiao Yang, Xuejiao Zhao, and Zhiqi Shen. 2025. Ageneralizable anomaly detection method in dynamic graphs. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 39. 22001-22009."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3368111"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3729224"},{"key":"e_1_3_2_1_48_1","volume-title":"Graph2text or graph2token: A perspective of large language models for graph learning. ACM Transactions on Information Systems","author":"Yu Shuo","year":"2025","unstructured":"Shuo Yu, Yingbo Wang, Ruolin Li, Guchun Liu, Yanming Shen, Shaoxiong Ji, Bowen Li, Fengling Han, Xiuzhen Zhang, and Feng Xia. 2025. Graph2text or graph2token: A perspective of large language models for graph learning. ACM Transactions on Information Systems (2025)."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2025.3540796"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/1052812.1052825"},{"key":"e_1_3_2_1_51_1","volume-title":"Knowledge-aware neural networks with personalized feature referencing for cold-start recommendation. arXiv preprint arXiv:2209.13973","author":"Zhang Xinni","year":"2022","unstructured":"Xinni Zhang, Yankai Chen, Cuiyun Gao, Qing Liao, Shenglin Zhao, and Irwin King. 2022. Knowledge-aware neural networks with personalized feature referencing for cold-start recommendation. arXiv preprint arXiv:2209.13973 (2022)."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657748"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657761"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671913"},{"key":"e_1_3_2_1_55_1","volume-title":"COIN-GNN: Inductive Spatial-Temporal Prediction for Continuous Distribution Shifts via Graph Neural Networks","author":"Zheng Jialun","year":"2025","unstructured":"Jialun Zheng, Divya Saxena, and Jiannong Cao. 2025. COIN-GNN: Inductive Spatial-Temporal Prediction for Continuous Distribution Shifts via Graph Neural Networks. IEEE Transactions on Knowledge and Data Engineering (2025)."},{"key":"e_1_3_2_1_56_1","volume-title":"Inductive Spatial Temporal Prediction Under Data Drift with Informative Graph Neural Network. In International Conference on Database Systems for Advanced Applications. Springer, 169-185","author":"Zheng Jialun","year":"2024","unstructured":"Jialun Zheng, Divya Saxena, Jiannong Cao, Hanchen Yang, and Penghui Ruan. 2024. Inductive Spatial Temporal Prediction Under Data Drift with Informative Graph Neural Network. In International Conference on Database Systems for Advanced Applications. Springer, 169-185."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01688"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671777"}],"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\/3774904.3792268","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T13:57:15Z","timestamp":1777298235000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774904.3792268"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":58,"alternative-id":["10.1145\/3774904.3792268","10.1145\/3774904"],"URL":"https:\/\/doi.org\/10.1145\/3774904.3792268","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"}}]}}