{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:01:34Z","timestamp":1772906494786,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":48,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T00:00:00Z","timestamp":1745280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Scientific Research Project of National University of Defense Technology","award":["ZK22-11"],"award-info":[{"award-number":["ZK22-11"]}]},{"name":"Basic Strengthening Program (Young Elite Scientists Sponsorship Program)","award":["2023-JCJQ-QT-048"],"award-info":[{"award-number":["2023-JCJQ-QT-048"]}]},{"DOI":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372458, 62272262, 62302511"],"award-info":[{"award-number":["62372458, 62272262, 62302511"]}],"id":[{"id":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Scientific Research Innovation Project of Hunan Province","award":["CX20230083"],"award-info":[{"award-number":["CX20230083"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,4,28]]},"DOI":"10.1145\/3696410.3714712","type":"proceedings-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T22:52:18Z","timestamp":1745362338000},"page":"4101-4110","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["On the Cross-Graph Transferability of Dynamic Link Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5484-1743","authenticated-orcid":false,"given":"Zhiqiang","family":"Pan","sequence":"first","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering, National University of Defense Technology, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7561-5646","authenticated-orcid":false,"given":"Chen","family":"Gao","sequence":"additional","affiliation":[{"name":"Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9221-5731","authenticated-orcid":false,"given":"Fei","family":"Cai","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering, National University of Defense Technology, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4470-9655","authenticated-orcid":false,"given":"Wanyu","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Electronic Countermeasures, National University of Defense Technology, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6070-1592","authenticated-orcid":false,"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering, National University of Defense Technology, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5234-0592","authenticated-orcid":false,"given":"Honghui","family":"Chen","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Information Systems Engineering, National University of Defense Technology, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5617-1659","authenticated-orcid":false,"given":"Yong","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,4,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3655103.3655110"},{"key":"e_1_3_2_1_2_1","volume-title":"The Eleventh International Conference on Learning Representations (ICLR).","author":"Cong Weilin","year":"2023","unstructured":"Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, and Mehrdad Mahdavi. 2023. Do We Really Need Complicated Model Architectures For Temporal Networks?. In The Eleventh International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_3_1","volume-title":"Alex Borges Vieira, and Artur Ziviani","author":"Tenorio de Barros Claudio Daniel","year":"2023","unstructured":"Claudio Daniel Tenorio de Barros, Matheus R. F. Mendon\u00e7a, Alex Borges Vieira, and Artur Ziviani. 2023. A Survey on Embedding Dynamic Graphs. ACM Comput. Surv., Vol. 55, 2 (2023), 10:1--10:37."},{"key":"e_1_3_2_1_4_1","volume-title":"Artificial Intelligence for Complex Network: Potential, Methodology and Application. arXiv preprint arXiv:2402.16887","author":"Ding Jingtao","year":"2024","unstructured":"Jingtao Ding, Chang Liu, Yu Zheng, Yunke Zhang, Zihan Yu, Ruikun Li, Hongyi Chen, Jinghua Piao, Huandong Wang, Jiazhen Liu, and Yong Li. 2024. Artificial Intelligence for Complex Network: Potential, Methodology and Application. arXiv preprint arXiv:2402.16887 (2024)."},{"key":"e_1_3_2_1_5_1","volume-title":"Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems (NeurIPS).","author":"Fan Shaohua","year":"2022","unstructured":"Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, and Jian Tang. 2022. Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_1_6_1","volume-title":"Kai Zheng, and Hongzhi Yin.","author":"Gao Xinyi","year":"2024","unstructured":"Xinyi Gao, Tong Chen, Yilong Zang, Wentao Zhang, Quoc Viet Hung Nguyen, Kai Zheng, and Hongzhi Yin. 2024. Graph Condensation for Inductive Node Representation Learning. (2024), 3056--3069."},{"key":"e_1_3_2_1_7_1","volume-title":"6th International Conference on Learning Representations (ICLR).","author":"Gidaris Spyros","year":"2018","unstructured":"Spyros Gidaris, Praveer Singh, and Nikos Komodakis. 2018. Unsupervised Representation Learning by Predicting Image Rotations. In 6th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645652"},{"key":"e_1_3_2_1_9_1","volume-title":"One Graph Model for Cross-domain Dynamic Link Prediction. arXiv preprint arXiv:2402.02168","author":"Huang Xuanwen","year":"2024","unstructured":"Xuanwen Huang, Wei Chow, Yang Wang, Ziwei Chai, Chunping Wang, Lei Chen, and Yang Yang. 2024a. One Graph Model for Cross-domain Dynamic Link Prediction. arXiv preprint arXiv:2402.02168 (2024)."},{"key":"e_1_3_2_1_10_1","volume-title":"Large Language Models on Graphs: A Comprehensive Survey. arXiv preprint arXiv:2312.02783","author":"Jin Bowen","year":"2023","unstructured":"Bowen Jin, Gang Liu, Chi Han, Meng Jiang, Heng Ji, and Jiawei Han. 2023. Large Language Models on Graphs: A Comprehensive Survey. arXiv preprint arXiv:2312.02783 (2023)."},{"key":"e_1_3_2_1_11_1","unstructured":"Ming Jin Yuan-Fang Li and Shirui Pan. 2022a. Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_1_12_1","volume-title":"Graph Condensation for Graph Neural Networks. In The Tenth International Conference on Learning Representations (ICLR).","author":"Jin Wei","year":"2022","unstructured":"Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, and Neil Shah. 2022b. Graph Condensation for Graph Neural Networks. In The Tenth International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_13_1","article-title":"Representation Learning for Dynamic Graphs: A Survey","volume":"21","author":"Kazemi Seyed Mehran","year":"2020","unstructured":"Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, and Pascal Poupart. 2020. Representation Learning for Dynamic Graphs: A Survey. J. Mach. Learn. Res., Vol. 21 (2020), 70:1--70:73.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3633518"},{"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":"crossref","unstructured":"Aming Li Lei Zhou Qi Su et al. 2020. Evolution of cooperation on temporal networks. Nature communications Vol. 11 1 (2020) 2259.","DOI":"10.1038\/s41467-020-16088-w"},{"key":"e_1_3_2_1_17_1","volume-title":"Let Invariant Rationale Discovery Inspire Graph Contrastive Learning. In International Conference on Machine Learning (ICML) (Proceedings of Machine Learning Research)","volume":"162","author":"Li Sihang","year":"2022","unstructured":"Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, and Tat-Seng Chua. 2022. Let Invariant Rationale Discovery Inspire Graph Contrastive Learning. In International Conference on Machine Learning (ICML) (Proceedings of Machine Learning Research), Vol. 162. PMLR, 13052--13065."},{"key":"e_1_3_2_1_18_1","volume-title":"Neural Predicting Higher-order Patterns in Temporal Networks. In The ACM Web Conference (WWW). ACM, 1340--1351","author":"Liu Yunyu","year":"2022","unstructured":"Yunyu Liu, Jianzhu Ma, and Pan Li. 2022. Neural Predicting Higher-order Patterns in Temporal Networks. In The ACM Web Conference (WWW). ACM, 1340--1351."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357943"},{"key":"e_1_3_2_1_20_1","volume-title":"Learning Causal Effects on Hypergraphs. In The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). ACM, 1202--1212","author":"Ma Jing","year":"2022","unstructured":"Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, and Jaime Teevan. 2022. Learning Causal Effects on Hypergraphs. In The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). ACM, 1202--1212."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3328924"},{"key":"e_1_3_2_1_22_1","unstructured":"Judea Pearl. 2009. Causality. Cambridge university press."},{"key":"e_1_3_2_1_23_1","volume-title":"Towards Better Evaluation for Dynamic Link Prediction. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems (NeurIPS).","author":"Poursafaei Farimah","year":"2022","unstructured":"Farimah Poursafaei, Shenyang Huang, Kellin Pelrine, and Reihaneh Rabbany. 2022. Towards Better Evaluation for Dynamic Link Prediction. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems (NeurIPS). Curran Associates, Inc., 1177--1184","author":"Rahimi Ali","year":"2007","unstructured":"Ali Rahimi and Benjamin Recht. 2007. Random Features for Large-Scale Kernel Machines. In Advances in Neural Information Processing Systems 20, Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems (NeurIPS). Curran Associates, Inc., 1177--1184."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591665"},{"key":"e_1_3_2_1_26_1","volume-title":"Bronstein","author":"Rossi Emanuele","year":"2020","unstructured":"Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, and Michael M. Bronstein. 2020. Temporal Graph Networks for Deep Learning on Dynamic Graphs. arXiv preprint arXiv:2006.10637 (2020)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1602803113"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3648156"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615032"},{"key":"e_1_3_2_1_30_1","volume-title":"DDGCN: Dual Dynamic Graph Convolutional Networks for Rumor Detection on Social Media. In Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI","author":"Sun Mengzhu","year":"2022","unstructured":"Mengzhu Sun, Xi Zhang, Jiaqi Zheng, and Guixiang Ma. 2022. DDGCN: Dual Dynamic Graph Convolutional Networks for Rumor Detection on Social Media. In Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence, IAAI 2022, The Twelveth Symposium on Educational Advances in Artificial Intelligence, EAAI 2022 Virtual Event, February 22 - March 1, 2022. AAAI Press, 4611--4619."},{"key":"e_1_3_2_1_31_1","volume-title":"FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction. In The Twelfth International Conference on Learning Representations (ICLR).","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 (ICLR)."},{"key":"e_1_3_2_1_32_1","volume-title":"Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems (NeurIPS). 24261--24272","author":"Tolstikhin Ilya O.","year":"2021","unstructured":"Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, and Alexey Dosovitskiy. 2021. MLP-Mixer: An all-MLP Architecture for Vision. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems (NeurIPS). 24261--24272."},{"key":"e_1_3_2_1_33_1","volume-title":"7th International Conference on Learning Representations (ICLR).","author":"Trivedi Rakshit","year":"2019","unstructured":"Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, and Hongyuan Zha. 2019. DyRep: Learning Representations over Dynamic Graphs. In 7th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_34_1","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems (NeurIPS). 5998--6008","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems (NeurIPS). 5998--6008."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401133"},{"key":"e_1_3_2_1_36_1","volume-title":"TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning. arXiv preprint arXiv:2105.07944","author":"Wang Lu","year":"2021","unstructured":"Lu Wang, Xiaofu Chang, Shuang Li, Yunfei Chu, Hui Li, Wei Zhang, Xiaofeng He, Le Song, Jingren Zhou, and Hongxia Yang. 2021a. TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning. arXiv preprint arXiv:2105.07944 (2021)."},{"key":"e_1_3_2_1_37_1","volume-title":"9th International Conference on Learning Representations (ICLR).","author":"Wang Yanbang","year":"2021","unstructured":"Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, and Pan Li. 2021b. Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks. In 9th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_38_1","volume-title":"TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Networks. In The Web Conference (WWW). ACM \/ IW3C2, 693--705","author":"Wang Yanbang","year":"2021","unstructured":"Yanbang Wang, Pan Li, Chongyang Bai, and Jure Leskovec. 2021c. TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Networks. In The Web Conference (WWW). ACM \/ IW3C2, 693--705."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557301"},{"key":"e_1_3_2_1_40_1","volume-title":"Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. In The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). ACM, 1791--1800","author":"Wei Tianxin","year":"2021","unstructured":"Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, and Xiangnan He. 2021. Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. In The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). ACM, 1791--1800."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"e_1_3_2_1_42_1","volume-title":"Self-attention with Functional Time Representation Learning. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems (NeurIPS). 15889--15899","author":"Xu Da","year":"2019","unstructured":"Da Xu, Chuanwei Ruan, Evren K\u00f6rpeoglu, Sushant Kumar, and Kannan Achan. 2019. Self-attention with Functional Time Representation Learning. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems (NeurIPS). 15889--15899."},{"key":"e_1_3_2_1_43_1","volume-title":"8th International Conference on Learning Representations (ICLR).","author":"Xu Da","year":"2020","unstructured":"Da Xu, Chuanwei Ruan, Evren K\u00f6rpeoglu, Sushant Kumar, and Kannan Achan. 2020. Inductive representation learning on temporal graphs. In 8th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_44_1","volume-title":"A Diffusive Data Augmentation Framework for Reconstruction of Complex Network Evolutionary History. arXiv preprint arXiv:2501.06485","author":"Xu En","year":"2025","unstructured":"En Xu, Can Rong, Jingtao Ding, and Yong Li. 2025. A Diffusive Data Augmentation Framework for Reconstruction of Complex Network Evolutionary History. arXiv preprint arXiv:2501.06485 (2025)."},{"key":"e_1_3_2_1_45_1","volume-title":"Few-shot Link Prediction in Dynamic Networks. In The Fifteenth ACM International Conference on Web Search and Data Mining (WSDM). ACM, 1245--1255","author":"Yang Cheng","year":"2022","unstructured":"Cheng Yang, Chunchen Wang, Yuanfu Lu, Xumeng Gong, Chuan Shi, Wei Wang, and Xu Zhang. 2022. Few-shot Link Prediction in Dynamic Networks. In The Fifteenth ACM International Conference on Web Search and Data Mining (WSDM). ACM, 1245--1255."},{"key":"e_1_3_2_1_46_1","unstructured":"Le Yu Leilei Sun Bowen Du and Weifeng Lv. 2023. Towards Better Dynamic Graph Learning: New Architecture and Unified Library. (2023)."},{"key":"e_1_3_2_1_47_1","volume-title":"Causal Intervention for Leveraging Popularity Bias in Recommendation. In The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). ACM, 11--20","author":"Zhang Yang","year":"2021","unstructured":"Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling, and Yongdong Zhang. 2021. Causal Intervention for Leveraging Popularity Bias in Recommendation. In The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). ACM, 11--20."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3672001"}],"event":{"name":"WWW '25: The ACM Web Conference 2025","location":"Sydney NSW Australia","acronym":"WWW '25","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM on Web Conference 2025"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696410.3714712","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3696410.3714712","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:57Z","timestamp":1750295937000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696410.3714712"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,22]]},"references-count":48,"alternative-id":["10.1145\/3696410.3714712","10.1145\/3696410"],"URL":"https:\/\/doi.org\/10.1145\/3696410.3714712","relation":{},"subject":[],"published":{"date-parts":[[2025,4,22]]},"assertion":[{"value":"2025-04-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}