{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:27:27Z","timestamp":1772908047608,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":23,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing Natural Science Foundation","award":["IS23128,"],"award-info":[{"award-number":["IS23128,"]}]},{"name":"Technology and Innovation Major Project of the Ministry of Science and Technology of China","award":["2020AAA0108404"],"award-info":[{"award-number":["2020AAA0108404"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,7,10]]},"DOI":"10.1145\/3626772.3657913","type":"proceedings-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T12:40:05Z","timestamp":1720701605000},"page":"2457-2461","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["IdmGAE: Importance-Inspired Dynamic Masking for Graph Autoencoders"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7502-8852","authenticated-orcid":false,"given":"Ge","family":"Chen","sequence":"first","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7598-8279","authenticated-orcid":false,"given":"Yulan","family":"Hu","sequence":"additional","affiliation":[{"name":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1502-5707","authenticated-orcid":false,"given":"Sheng","family":"Ouyang","sequence":"additional","affiliation":[{"name":"Gaoling Artificial Intelligence School of Renmin University, Renmin University of China, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1017-4677","authenticated-orcid":false,"given":"Zhirui","family":"Yang","sequence":"additional","affiliation":[{"name":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6739-621X","authenticated-orcid":false,"given":"Yong","family":"Liu","sequence":"additional","affiliation":[{"name":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4570-5990","authenticated-orcid":false,"given":"Cuicui","family":"Luo","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,7,11]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Patel","author":"Chaminda Bandara Wele Gedara","year":"2022","unstructured":"Wele Gedara Chaminda Bandara, Naman Patel, Ali Gholami, Mehdi Nikkhah, Motilal Agrawal, and Vishal M. Patel. 2022. AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders. arxiv: 2211.09120 [cs.CV]"},{"key":"e_1_3_2_1_2_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arxiv","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arxiv: 1810.04805 [cs.CL]"},{"key":"e_1_3_2_1_3_1","volume-title":"International conference on machine learning. PMLR, 4116--4126","author":"Hassani Kaveh","year":"2020","unstructured":"Kaveh Hassani and Amir Hosein Khasahmadi. 2020. Contrastive multi-view representation learning on graphs. In International conference on machine learning. PMLR, 4116--4126."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"e_1_3_2_1_5_1","unstructured":"Zhenyu Hou Yufei He Yukuo Cen Xiao Liu Yuxiao Dong Evgeny Kharlamov and Jie Tang. 2023. GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner. arxiv: 2304.04779 [cs.LG]"},{"key":"e_1_3_2_1_6_1","unstructured":"Zhenyu Hou Xiao Liu Yukuo Cen Yuxiao Dong Hongxia Yang Chunjie Wang and Jie Tang. 2022. GraphMAE: Self-Supervised Masked Graph Autoencoders. arxiv: 2205.10803 [cs.LG]"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20056-4_18"},{"key":"e_1_3_2_1_8_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2017","unstructured":"Diederik P. Kingma and Jimmy Ba. 2017. Adam: A Method for Stochastic Optimization. arxiv: 1412.6980 [cs.LG]"},{"key":"e_1_3_2_1_9_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2016","unstructured":"Thomas N. Kipf and Max Welling. 2016. Variational Graph Auto-Encoders. arxiv: 1611.07308 [stat.ML]"},{"key":"e_1_3_2_1_10_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2017","unstructured":"Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. arxiv: 1609.02907 [cs.LG]"},{"key":"e_1_3_2_1_11_1","unstructured":"Xiang Li Tiandi Ye Caihua Shan Dongsheng Li and Ming Gao. 2023. SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking. arxiv: 2301.12458 [cs.LG]"},{"key":"e_1_3_2_1_12_1","volume-title":"MST: Masked Self-Supervised Transformer for Visual Representation. arxiv: 2106.05656 [cs.CV]","author":"Li Zhaowen","year":"2021","unstructured":"Zhaowen Li, Zhiyang Chen, Fan Yang, Wei Li, Yousong Zhu, Chaoyang Zhao, Rui Deng, Liwei Wu, Rui Zhao, Ming Tang, and Jinqiao Wang. 2021. MST: Masked Self-Supervised Transformer for Visual Representation. arxiv: 2106.05656 [cs.CV]"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.2307\/2985612"},{"key":"e_1_3_2_1_14_1","volume-title":"Kosiorek","author":"Shi Yuge","year":"2022","unstructured":"Yuge Shi, N. Siddharth, Philip H. S. Torr, and Adam R. Kosiorek. 2022. Adversarial Masking for Self-Supervised Learning. arxiv: 2201.13100 [cs.CV]"},{"key":"e_1_3_2_1_15_1","volume-title":"Policy gradient methods for reinforcement learning with function approximation (NIPS'99)","author":"Sutton Richard S.","unstructured":"Richard S. Sutton, David McAllester, Satinder Singh, and Yishay Mansour. 1999. Policy gradient methods for reinforcement learning with function approximation (NIPS'99). MIT Press, Cambridge, MA, USA, 7 pages."},{"key":"e_1_3_2_1_16_1","volume-title":"MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs. arxiv: 2201.02534 [cs.LG]","author":"Tan Qiaoyu","year":"2022","unstructured":"Qiaoyu Tan, Ninghao Liu, Xiao Huang, Rui Chen, Soo-Hyun Choi, and Xia Hu. 2022. MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs. arxiv: 2201.02534 [cs.LG]"},{"key":"e_1_3_2_1_17_1","unstructured":"Petar Veli\u010dkovi\u0107 Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Li\u00f2 and Yoshua Bengio. 2018a. Graph Attention Networks. arxiv: 1710.10903 [stat.ML]"},{"key":"e_1_3_2_1_18_1","volume-title":"Deep Graph Infomax. arxiv","author":"Veli\u010dkovi\u0107 Petar","year":"1809","unstructured":"Petar Veli\u010dkovi\u0107, William Fedus, William L. Hamilton, Pietro Li\u00f2, Yoshua Bengio, and R Devon Hjelm. 2018b. Deep Graph Infomax. arxiv: 1809.10341 [stat.ML]"},{"key":"e_1_3_2_1_19_1","unstructured":"Liang Wang Xiang Tao Qiang Liu Shu Wu and Liang Wang. 2024. Rethinking Graph Masked Autoencoders through Alignment and Uniformity. arxiv: 2402.07225 [cs.LG]"},{"key":"e_1_3_2_1_20_1","first-page":"76","article-title":"From canonical correlation analysis to self-supervised graph neural networks","volume":"34","author":"Zhang Hengrui","year":"2021","unstructured":"Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, and Philip S Yu. 2021. From canonical correlation analysis to self-supervised graph neural networks. Advances in Neural Information Processing Systems, Vol. 34 (2021), 76--89.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_21_1","unstructured":"Qi Zhang Yifei Wang and Yisen Wang. 2023. How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders. arxiv: 2210.08344 [cs.LG]"},{"key":"e_1_3_2_1_22_1","volume-title":"Deep graph contrastive representation learning. arXiv preprint arXiv:2006.04131","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. arXiv preprint arXiv:2006.04131 (2020)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449802"}],"event":{"name":"SIGIR 2024: The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Washington DC USA","acronym":"SIGIR 2024","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657913","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3626772.3657913","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:20:59Z","timestamp":1755840059000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657913"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,10]]},"references-count":23,"alternative-id":["10.1145\/3626772.3657913","10.1145\/3626772"],"URL":"https:\/\/doi.org\/10.1145\/3626772.3657913","relation":{},"subject":[],"published":{"date-parts":[[2024,7,10]]},"assertion":[{"value":"2024-07-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}