{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T02:47:23Z","timestamp":1783738043678,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":61,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T00:00:00Z","timestamp":1689638400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,7,19]]},"DOI":"10.1145\/3539618.3591652","type":"proceedings-article","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T00:22:23Z","timestamp":1689726143000},"page":"601-611","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":40,"title":["Continual Learning on Dynamic Graphs via Parameter Isolation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8691-1846","authenticated-orcid":false,"given":"Peiyan","family":"Zhang","sequence":"first","affiliation":[{"name":"Hong Kong University of Science and Technology, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8672-4468","authenticated-orcid":false,"given":"Yuchen","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Intelligence Science and Technology, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9867-1712","authenticated-orcid":false,"given":"Chaozhuo","family":"Li","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3615-4859","authenticated-orcid":false,"given":"Senzhang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8608-8482","authenticated-orcid":false,"given":"Xing","family":"Xie","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8295-2520","authenticated-orcid":false,"given":"Guojie","family":"Song","sequence":"additional","affiliation":[{"name":"School of Intelligence Science and Technology, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8002-2485","authenticated-orcid":false,"given":"Sunghun","family":"Kim","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,7,18]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_9"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_33"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/288"},{"key":"e_1_3_2_1_4_1","volume-title":"Pathnet: Evolution channels gradient descent in super neural networks. arXiv preprint arXiv:1701.08734","author":"Fernando Chrisantha","year":"2017","unstructured":"Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A Rusu, Alexander Pritzel, and Daan Wierstra. 2017. Pathnet: Evolution channels gradient descent in super neural networks. arXiv preprint arXiv:1701.08734 (2017)."},{"key":"e_1_3_2_1_5_1","volume-title":"Catastrophic forgetting in connectionist networks. Trends in cognitive sciences","author":"French Robert M","year":"1999","unstructured":"Robert M French. 1999. Catastrophic forgetting in connectionist networks. Trends in cognitive sciences, Vol. 3, 4 (1999), 128--135."},{"key":"e_1_3_2_1_6_1","volume-title":"DynGEM: Deep Embedding Method for Dynamic Graphs. CoRR","author":"Goyal Palash","year":"2018","unstructured":"Palash Goyal, Nitin Kamra, Xinran He, and Yan Liu. 2018. DynGEM: Deep Embedding Method for Dynamic Graphs. CoRR, Vol. abs\/1805.11273 (2018). arxiv: 1805.11273"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_1_8_1","volume-title":"Homophily-oriented Heterogeneous Graph Rewiring. arXiv preprint arXiv:2302.06299","author":"Guo Jiayan","year":"2023","unstructured":"Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, and Yan Zhang. 2023. Homophily-oriented Heterogeneous Graph Rewiring. arXiv preprint arXiv:2302.06299 (2023)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498524"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557314"},{"key":"e_1_3_2_1_11_1","unstructured":"Ehsan Hajiramezanali Arman Hasanzadeh Krishna R. Narayanan Nick Duffield Mingyuan Zhou and Xiaoning Qian. 2019. Variational Graph Recurrent Neural Networks. In Advances in Neural Information Processing Systems. 10700--10710."},{"key":"e_1_3_2_1_12_1","volume-title":"Inductive representation learning on large graphs. Advances in neural information processing systems","author":"Hamilton Will","year":"2017","unstructured":"Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_14_1","volume-title":"Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531","author":"Hinton Geoffrey","year":"2015","unstructured":"Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)."},{"key":"e_1_3_2_1_15_1","volume-title":"International Conference on Machine Learning. PMLR, 9377--9409","author":"Huang Zhongyu","year":"2022","unstructured":"Zhongyu Huang, Yingheng Wang, Chaozhuo Li, and Huiguang He. 2022. Going Deeper into Permutation-Sensitive Graph Neural Networks. In International Conference on Machine Learning. PMLR, 9377--9409."},{"key":"e_1_3_2_1_16_1","volume-title":"picking and growing for unforgetting continual learning. arXiv preprint arXiv:1910.06562","author":"Hung Steven CY","year":"2019","unstructured":"Steven CY Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen. 2019. Compacting, picking and growing for unforgetting continual learning. arXiv preprint arXiv:1910.06562 (2019)."},{"key":"e_1_3_2_1_17_1","first-page":"18493","article-title":"Continual learning of a mixed sequence of similar and dissimilar tasks","volume":"33","author":"Ke Zixuan","year":"2020","unstructured":"Zixuan Ke, Bing Liu, and Xingchang Huang. 2020. Continual learning of a mixed sequence of similar and dissimilar tasks. Advances in Neural Information Processing Systems, Vol. 33 (2020), 18493--18504.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_18_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"e_1_3_2_1_20_1","volume-title":"Fast and uncertainty-aware directional message passing for non-equilibrium molecules. arXiv preprint arXiv:2011.14115","author":"Klicpera Johannes","year":"2020","unstructured":"Johannes Klicpera, Shankari Giri, Johannes T Margraf, and Stephan G\u00fcnnemann. 2020a. Fast and uncertainty-aware directional message passing for non-equilibrium molecules. arXiv preprint arXiv:2011.14115 (2020)."},{"key":"e_1_3_2_1_21_1","volume-title":"Directional message passing for molecular graphs. arXiv preprint arXiv:2003.03123","author":"Klicpera Johannes","year":"2020","unstructured":"Johannes Klicpera, Janek Gro\u00df, and Stephan G\u00fcnnemann. 2020b. Directional message passing for molecular graphs. arXiv preprint arXiv:2003.03123 (2020)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.237"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"e_1_3_2_1_24_1","volume-title":"International Conference on Machine Learning. PMLR, 13209--13224","author":"Li Rui","year":"2022","unstructured":"Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, et al. 2022. House: Knowledge graph embedding with householder parameterization. In International Conference on Machine Learning. PMLR, 13209--13224."},{"key":"e_1_3_2_1_25_1","volume-title":"Learning without forgetting","author":"Li Zhizhong","year":"2017","unstructured":"Zhizhong Li and Derek Hoiem. 2017. Learning without forgetting. IEEE transactions on pattern analysis and machine intelligence, Vol. 40, 12 (2017), 2935--2947."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17049"},{"key":"e_1_3_2_1_27_1","volume-title":"Gradient episodic memory for continual learning. arXiv preprint arXiv:1706.08840","author":"Lopez-Paz David","year":"2017","unstructured":"David Lopez-Paz and Marc'Aurelio Ranzato. 2017. Gradient episodic memory for continual learning. arXiv preprint arXiv:1706.08840 (2017)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512100"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401092"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009953814988"},{"key":"e_1_3_2_1_31_1","volume-title":"Psychology of learning and motivation.","author":"McCloskey Michael","unstructured":"Michael McCloskey and Neal J Cohen. 1989. Catastrophic interference in connectionist networks: The sequential learning problem. In Psychology of learning and motivation. Vol. 24. Elsevier, 109--165."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539128"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"e_1_3_2_1_35_1","volume-title":"Model Zoo: A Growing Brain That Learns Continually. In NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and Applications.","author":"Ramesh Rahul","year":"2021","unstructured":"Rahul Ramesh and Pratik Chaudhari. 2021. Model Zoo: A Growing Brain That Learns Continually. In NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and Applications."},{"key":"e_1_3_2_1_36_1","volume-title":"Connectionist models of recognition memory: constraints imposed by learning and forgetting functions. Psychological review","author":"Ratcliff Roger","year":"1990","unstructured":"Roger Ratcliff. 1990. Connectionist models of recognition memory: constraints imposed by learning and forgetting functions. Psychological review, Vol. 97, 2 (1990), 285."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.587"},{"key":"e_1_3_2_1_38_1","volume-title":"Experience replay for continual learning. arXiv preprint arXiv:1811.11682","author":"Rolnick David","year":"2018","unstructured":"David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P Lillicrap, and Greg Wayne. 2018. Experience replay for continual learning. arXiv preprint arXiv:1811.11682 (2018)."},{"key":"e_1_3_2_1_39_1","volume-title":"Incremental learning through deep adaptation","author":"Rosenfeld Amir","year":"2018","unstructured":"Amir Rosenfeld and John K Tsotsos. 2018. Incremental learning through deep adaptation. IEEE transactions on pattern analysis and machine intelligence, Vol. 42, 3 (2018), 651--663."},{"key":"e_1_3_2_1_40_1","volume-title":"Progressive neural networks. arXiv preprint arXiv:1606.04671","author":"Rusu Andrei A","year":"2016","unstructured":"Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell. 2016. Progressive neural networks. arXiv preprint arXiv:1606.04671 (2016)."},{"key":"e_1_3_2_1_41_1","volume-title":"Collective classification in network data. AI magazine","author":"Sen Prithviraj","year":"2008","unstructured":"Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Galligher, and Tina Eliassi-Rad. 2008. Collective classification in network data. AI magazine, Vol. 29, 3 (2008), 93--93."},{"key":"e_1_3_2_1_42_1","volume-title":"Pitfalls of graph neural network evaluation. arXiv preprint arXiv:1811.05868","author":"Shchur Oleksandr","year":"2018","unstructured":"Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, and Stephan G\u00fcnnemann. 2018. Pitfalls of graph neural network evaluation. arXiv preprint arXiv:1811.05868 (2018)."},{"key":"e_1_3_2_1_43_1","volume-title":"Advances in Neural Information Processing Systems","volume":"34","author":"Shi Guangyuan","year":"2021","unstructured":"Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, and Xiao-Ming Wu. 2021. Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima. Advances in Neural Information Processing Systems, Vol. 34 (2021)."},{"key":"e_1_3_2_1_44_1","volume-title":"Jaehong Kim, and Jiwon Kim.","author":"Shin Hanul","year":"2017","unstructured":"Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim. 2017. Continual learning with deep generative replay. arXiv preprint arXiv:1705.08690 (2017)."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/640"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1402008"},{"key":"e_1_3_2_1_48_1","volume-title":"International conference on learning representations.","author":"Trivedi Rakshit","year":"2019","unstructured":"Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, and Hongyuan Zha. 2019. Dyrep: Learning representations over dynamic graphs. In International conference on learning representations."},{"key":"e_1_3_2_1_49_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Petar Velivc","year":"2017","unstructured":"Petar Velivc kovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411963"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1162\/qss_a_00021"},{"key":"e_1_3_2_1_52_1","volume-title":"Claudio Bellei, Tom Robinson, and Charles E Leiserson.","author":"Weber Mark","year":"2019","unstructured":"Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I Weidele, Claudio Bellei, Tom Robinson, and Charles E Leiserson. 2019. Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial forensics. arXiv preprint arXiv:1908.02591 (2019)."},{"key":"e_1_3_2_1_53_1","volume-title":"International conference on machine learning. PMLR, 6861--6871","author":"Wu Felix","year":"2019","unstructured":"Felix Wu, Amauri Souza, Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian Weinberger. 2019. Simplifying graph convolutional networks. In International conference on machine learning. PMLR, 6861--6871."},{"key":"e_1_3_2_1_54_1","volume-title":"How powerful are graph neural networks? arXiv preprint arXiv:1810.00826","author":"Xu Keyulu","year":"2018","unstructured":"Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2018. How powerful are graph neural networks? arXiv preprint arXiv:1810.00826 (2018)."},{"key":"e_1_3_2_1_55_1","volume-title":"Lifelong learning with dynamically expandable networks. arXiv preprint arXiv:1708.01547","author":"Yoon Jaehong","year":"2017","unstructured":"Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang. 2017. Lifelong learning with dynamically expandable networks. arXiv preprint arXiv:1708.01547 (2017)."},{"key":"e_1_3_2_1_56_1","volume-title":"International Conference on Machine Learning. PMLR, 3987--3995","author":"Zenke Friedemann","year":"2017","unstructured":"Friedemann Zenke, Ben Poole, and Surya Ganguli. 2017. Continual learning through synaptic intelligence. In International Conference on Machine Learning. PMLR, 3987--3995."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570445"},{"key":"e_1_3_2_1_58_1","volume-title":"A Survey on Incremental Update for Neural Recommender Systems. arXiv preprint arXiv:2303.02851","author":"Zhang Peiyan","year":"2023","unstructured":"Peiyan Zhang and Sunghun Kim. 2023. A Survey on Incremental Update for Neural Recommender Systems. arXiv preprint arXiv:2303.02851 (2023)."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531982"},{"key":"e_1_3_2_1_60_1","volume-title":"Learning on Large-scale Text-attributed Graphs via Variational Inference. arXiv preprint arXiv:2210.14709","author":"Zhao Jianan","year":"2022","unstructured":"Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, and Jian Tang. 2022. Learning on Large-scale Text-attributed Graphs via Variational Inference. arXiv preprint arXiv:2210.14709 (2022)."},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16602"}],"event":{"name":"SIGIR '23: The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Taipei Taiwan","acronym":"SIGIR '23","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539618.3591652","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3539618.3591652","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:40Z","timestamp":1750182700000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539618.3591652"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,18]]},"references-count":61,"alternative-id":["10.1145\/3539618.3591652","10.1145\/3539618"],"URL":"https:\/\/doi.org\/10.1145\/3539618.3591652","relation":{},"subject":[],"published":{"date-parts":[[2023,7,18]]},"assertion":[{"value":"2023-07-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}