{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T20:24:26Z","timestamp":1787689466109,"version":"build-2784847793"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","funder":[{"name":"National Natural Science Foundation of China","award":["62002047"],"award-info":[{"award-number":["62002047"]}]},{"name":"National Natural Science Foundation of China","award":["62572244"],"award-info":[{"award-number":["62572244"]}]},{"name":"National Natural Science Foundation of China","award":["62502298"],"award-info":[{"award-number":["62502298"]}]},{"name":"National Research Foundation, Singapore, and Cyber Security Agency of Singapore under its National Cybersecurity R\\&D Programme and CyberSG R\\&D Cyber Research Programme Office","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]},{"name":"Natural Science Foundation of Shanghai","award":["24ZR1421500"],"award-info":[{"award-number":["24ZR1421500"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,8,9]]},"DOI":"10.1145\/3770854.3780269","type":"proceedings-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T12:07:40Z","timestamp":1785499660000},"page":"59-70","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Two Heads Are Better Than One: Generalized Cross-Domain Federated Learning via Dual-Prototype"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0691-2724","authenticated-orcid":false,"given":"Mingsheng","family":"Cao","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6063-7238","authenticated-orcid":false,"given":"Tianci","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5058-4660","authenticated-orcid":false,"given":"Ming","family":"Hu","sequence":"additional","affiliation":[{"name":"East China Normal University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3433-7413","authenticated-orcid":false,"given":"Zhuang","family":"Qi","sequence":"additional","affiliation":[{"name":"Shandong University, Jinan, Shandong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0411-6461","authenticated-orcid":false,"given":"Yangguang","family":"Cui","sequence":"additional","affiliation":[{"name":"Shanghai University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7734-4077","authenticated-orcid":false,"given":"Junlong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1288-6502","authenticated-orcid":false,"given":"Xiaofei","family":"Xie","sequence":"additional","affiliation":[{"name":"Singapore Management University, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,20]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"PMLR","author":"McMahan Brendan","year":"2017","unstructured":"Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas. Communication-efficient learning of deep networks from decentralized data. In Artificial intelligence and statistics, pages 1273-1282. PMLR, 2017."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3418862"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3672042"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671908"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.52202\/079017-4439"},{"key":"e_1_3_2_2_6_1","volume-title":"Forty-second International Conference on Machine Learning.","author":"Zhang Jiayuan","unstructured":"Jiayuan Zhang, Xuefeng Liu, Jianwei Niu, Shaojie Tang, Haotian Yang, and Xinghao Wu. Causality inspired federated learning for ood generalization. In Forty-second International Conference on Machine Learning."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2025.3624064"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3649329.3655917"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/RTSS59052.2023.00022"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2024.3444695"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671702"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3711896.3736987"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i27.35054"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.00954"},{"key":"e_1_3_2_2_15_1","first-page":"5132","volume-title":"International conference on machine learning","author":"Karimireddy Sai Praneeth","year":"2020","unstructured":"Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank Reddi, Sebastian Stich, and Ananda Theertha Suresh. Scaffold: Stochastic controlled averaging for federated learning. In International conference on machine learning, pages 5132-5143. PMLR, 2020."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICME55011.2023.00117"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681260"},{"key":"e_1_3_2_2_18_1","first-page":"19986","volume-title":"AAAI","author":"Qi Zhuang","year":"2025","unstructured":"Zhuang Qi, Lei Meng, and et al. Cross-silo feature space alignment for federated learning on clients with imbalanced data. In AAAI, pages 19986-19994, 2025."},{"key":"e_1_3_2_2_19_1","unstructured":"Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar and Virginia Smith. Federated optimization in heterogeneous networks. Proceedings of Machine learning and systems 2:429-450 2020."},{"key":"e_1_3_2_2_20_1","first-page":"11058","volume-title":"International Conference on Machine Learning","author":"Kim Jinkyu","year":"2022","unstructured":"Jinkyu Kim, Geeho Kim, and Bohyung Han. Multi-level branched regularization for federated learning. In International Conference on Machine Learning, pages 11058-11073. PMLR, 2022."},{"key":"e_1_3_2_2_21_1","first-page":"12878","volume-title":"International conference on machine learning","author":"Zhu Zhuangdi","year":"2021","unstructured":"Zhuangdi Zhu, Junyuan Hong, and Jiayu Zhou. Data-free knowledge distillation for heterogeneous federated learning. In International conference on machine learning, pages 12878-12889. PMLR, 2021."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106627"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.52202\/075280-2639"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2022.3192506"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3366947"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE60146.2024.00170"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671722"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20819"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.52202\/079017-3757"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i15.29617"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.52202\/079017-2803"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01565"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58517-4_33"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00914"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.5555\/2354409.2355024"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00149"},{"key":"e_1_3_2_2_37_1","volume-title":"Fedfa: Federated feature augmentation. arXiv preprint arXiv:2301.12995","author":"Zhou Tianfei","year":"2023","unstructured":"Tianfei Zhou and Ender Konukoglu. Fedfa: Federated feature augmentation. arXiv preprint arXiv:2301.12995, 2023."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i11.29146"},{"key":"e_1_3_2_2_39_1","volume-title":"Federated learning from pre-trained models: A contrastive learning approach. Advances in neural information processing systems, 35:19332-19344","author":"Tan Yue","year":"2022","unstructured":"Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, and Jing Jiang. Federated learning from pre-trained models: A contrastive learning approach. Advances in neural information processing systems, 35:19332-19344, 2022."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25891"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i16.33829"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"}],"event":{"name":"KDD '26: The 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Jeju Island Republic of Korea","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3770854.3780269","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T20:03:12Z","timestamp":1787688192000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3770854.3780269"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,20]]},"references-count":42,"alternative-id":["10.1145\/3770854.3780269","10.1145\/3770854"],"URL":"https:\/\/doi.org\/10.1145\/3770854.3780269","relation":{},"subject":[],"published":{"date-parts":[[2026,4,20]]},"assertion":[{"value":"2026-04-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}