{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T19:10:02Z","timestamp":1755889802058,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,13]]},"DOI":"10.1145\/3726302.3730035","type":"proceedings-article","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T01:18:36Z","timestamp":1752455916000},"page":"750-760","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["MINTT: Memory Inductive Transfer for Temporal Graph Neural Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5056-6471","authenticated-orcid":false,"given":"Tanishq","family":"Dubey","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, New Delhi, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9838-125X","authenticated-orcid":false,"given":"Sidharth","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, New Delhi, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4710-3686","authenticated-orcid":false,"given":"Shubham","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, New Delhi, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3949-2175","authenticated-orcid":false,"given":"Srikanta","family":"Bedathur","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, New Delhi, India"}]}],"member":"320","published-online":{"date-parts":[[2025,7,13]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Sidharth Agarwal Tanishq Dubey Shubham Gupta and Srikanta Bedathur. 2025. A Transfer Framework for Enhancing Temporal Graph Learning in Data-Scarce Settings. arxiv:2503.00852 [cs.LG] https:\/\/arxiv.org\/abs\/2503.00852"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/45.329294"},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of the 35th International Conference on Machine Learning (Proceedings of Machine Learning Research","volume":"619","author":"Bojchevski Aleksandar","year":"2018","unstructured":"Aleksandar Bojchevski, Oleksandr Shchur, Daniel Z\u00fcgner, and Stephan G\u00fcnnemann. 2018. NetGAN: Generating Graphs via Random Walks. In Proceedings of the 35th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 80), Jennifer Dy and Andreas Krause (Eds.). PMLR, 610-619. https:\/\/proceedings.mlr.press\/v80\/bojchevski18a.html"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3560487"},{"key":"e_1_3_2_1_5_1","volume-title":"Graph Neural Networks for Link Prediction with Subgraph Sketching. In The Eleventh International Conference on Learning Representations, ICLR 2023","author":"Chamberlain Benjamin Paul","year":"2023","unstructured":"Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, and Max Hansmire. 2023. Graph Neural Networks for Link Prediction with Subgraph Sketching. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023. OpenReview.net. https:\/\/openreview.net\/forum?id=m1oqEOAozQU"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"e_1_3_2_1_7_1","volume-title":"The Eleventh International Conference on Learning Representations, ICLR 2023","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 2023, Kigali, Rwanda, May 1-5, 2023. OpenReview.net. https:\/\/openreview.net\/forum?id=ayPPc0SyLv1"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403113"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/3367243.3367352"},{"key":"e_1_3_2_1_10_1","volume-title":"Predicting a Business Star in Yelp from Its Reviews Text Alone. ArXiv","author":"Fan Mingming","year":"2014","unstructured":"Mingming Fan and Maryam Khademi. 2014. Predicting a Business Star in Yelp from Its Reviews Text Alone. ArXiv, Vol. abs\/1401.0864 (2014). https:\/\/api.semanticscholar.org\/CorpusID:7344916"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM51629.2021.00024"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3632410.3632464"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20638"},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 40th International Conference on Machine Learning","author":"Gupta Shubham","year":"2023","unstructured":"Shubham Gupta, Sahil Manchanda, Sayan Ranu, and Srikanta Bedathur. 2023. GRAFENNE: learning on graphs with heterogeneous and dynamic feature sets. In Proceedings of the 40th International Conference on Machine Learning (Honolulu, Hawaii, USA) (ICML'23). JMLR.org, Article 490, 17 pages."},{"key":"e_1_3_2_1_15_1","volume-title":"Inductive Representation Learning on Large Graphs. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017","author":"Hamilton William L.","year":"2017","unstructured":"William L. Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive Representation Learning on Large Graphs. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett (Eds.). 1024-1034. https:\/\/proceedings.neurips.cc\/paper\/2017\/hash\/5dd9db5e033da9c6fb5ba83c7a7ebea9-Abstract.html"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441738"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539250"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0155305"},{"key":"e_1_3_2_1_20_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. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings. OpenReview.net. https:\/\/openreview.net\/forum?id=SJU4ayYgl"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Nishai Kooverjee Steven James and Terence van Zyl. 2022. Investigating Transfer Learning in Graph Neural Networks. arxiv:2202.00740 [cs.LG]","DOI":"10.20944\/preprints202201.0457.v1"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"e_1_3_2_1_23_1","first-page":"519","volume-title":"Proceedings of the 18th International Joint Conference on Artificial Intelligence","author":"Ling Charles X.","year":"2003","unstructured":"Charles X. Ling, Jin Huang, and Harry Zhang. 2003. AUC: a statistically consistent and more discriminating measure than accuracy. In Proceedings of the 18th International Joint Conference on Artificial Intelligence (Acapulco, Mexico) (IJCAI'03). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 519-524."},{"key":"e_1_3_2_1_24_1","volume-title":"Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs","author":"Malkov Yu A","year":"2018","unstructured":"Yu A Malkov and Dmitry A Yashunin. 2018. Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE transactions on pattern analysis and machine intelligence, Vol. 42, 4 (2018), 824-836."},{"key":"e_1_3_2_1_25_1","volume-title":"Learning on Graphs Conference. PMLR, 32-1.","author":"Manchanda Sahil","year":"2024","unstructured":"Sahil Manchanda, Shubham Gupta, Sayan Ranu, and Srikanta J Bedathur. 2024. Generative modeling of labeled graphs under data scarcity. In Learning on Graphs Conference. PMLR, 32-1."},{"key":"e_1_3_2_1_26_1","volume-title":"Temporal Graph Networks for Deep Learning on Dynamic Graphs. In ICML 2020 Workshop on Graph Representation Learning.","author":"Rossi Emanuele","year":"2020","unstructured":"Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, and Michael Bronstein. 2020. Temporal Graph Networks for Deep Learning on Dynamic Graphs. In ICML 2020 Workshop on Graph Representation Learning."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-022-00468-6"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01418-6_41"},{"key":"e_1_3_2_1_30_1","volume-title":"Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022","author":"Souza Amauri H.","year":"2022","unstructured":"Amauri H. Souza, Diego Mesquita, Samuel Kaski, and Vikas Garg. 2022. Provably expressive temporal graph networks. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, and A. Oh (Eds.). http:\/\/papers.nips.cc\/paper_files\/paper\/2022\/hash\/d029c97ee0db162c60f2ebc9cb93387e-Abstract-Conference.html"},{"key":"e_1_3_2_1_31_1","volume-title":"Advances in Neural Information Processing Systems","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, I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.), Vol. 30. Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2017\/file\/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf"},{"key":"e_1_3_2_1_32_1","volume-title":"6th International Conference on Learning Representations, ICLR","author":"Velickovic Petar","year":"2018","unstructured":"Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph Attention Networks. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings. OpenReview.net. https:\/\/openreview.net\/forum?id=rJXMpikCZ"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_34_1","unstructured":"Yanbang Wang Yen-Yu Chang Yunyu Liu Jure Leskovec and Pan Li. 2021. Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks. (2021). https:\/\/openreview.net\/forum?id=KYPz4YsCPj"},{"key":"e_1_3_2_1_35_1","volume-title":"8th International Conference on Learning Representations, ICLR 2020","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 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net. https:\/\/openreview.net\/forum?id=rJeW1yHYwH"},{"key":"e_1_3_2_1_36_1","volume-title":"7th International Conference on Learning Representations, ICLR 2019","author":"Xu Keyulu","year":"2019","unstructured":"Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2019. How Powerful are Graph Neural Networks?. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019. OpenReview.net. https:\/\/openreview.net\/forum?id=ryGs6iA5Km"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313635"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313577"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1609\/AAAI.V34I04.6142"},{"key":"e_1_3_2_1_40_1","first-page":"3320","volume-title":"Proceedings of the 27th International Conference on Neural Information Processing Systems -","volume":"2","author":"Yosinski Jason","year":"2014","unstructured":"Jason Yosinski, Jeff Clune, Yoshua Bengio, and Hod Lipson. 2014. How transferable are features in deep neural networks?. In Proceedings of the 27th International Conference on Neural Information Processing Systems - Volume 2 (Montreal, Canada) (NIPS'14). MIT Press, Cambridge, MA, USA, 3320-3328."},{"key":"e_1_3_2_1_41_1","volume-title":"ICML (Proceedings of Machine Learning Research","volume":"5703","author":"You Jiaxuan","year":"2018","unstructured":"Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, and Jure Leskovec. 2018. GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models. In ICML (Proceedings of Machine Learning Research, Vol. 80), Jennifer G. Dy and Andreas Krause (Eds.). PMLR, 5694-5703. http:\/\/dblp.uni-trier.de\/db\/conf\/icml\/icml2018.html#YouYRHL18"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.24963\/IJCAI.2018\/505"},{"key":"e_1_3_2_1_43_1","volume-title":"Towards Better Dynamic Graph Learning: New Architecture and Unified Library. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023","author":"Yu Le","year":"2023","unstructured":"Le Yu, Leilei Sun, Bowen Du, and Weifeng Lv. 2023. Towards Better Dynamic Graph Learning: New Architecture and Unified Library. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.). http:\/\/papers.nips.cc\/paper_files\/paper\/2023\/hash\/d611019afba70d547bd595e8a4158f55-Abstract-Conference.html"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220054"}],"event":{"name":"SIGIR '25: The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Padua Italy","acronym":"SIGIR '25"},"container-title":["Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3726302.3730035","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T18:29:36Z","timestamp":1755887376000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3726302.3730035"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,13]]},"references-count":44,"alternative-id":["10.1145\/3726302.3730035","10.1145\/3726302"],"URL":"https:\/\/doi.org\/10.1145\/3726302.3730035","relation":{},"subject":[],"published":{"date-parts":[[2025,7,13]]},"assertion":[{"value":"2025-07-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}