{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:28:57Z","timestamp":1781368137954,"version":"3.54.1"},"reference-count":39,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/icme59968.2025.11209067","type":"proceedings-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T17:57:42Z","timestamp":1761847062000},"page":"1-6","source":"Crossref","is-referenced-by-count":1,"title":["RoGA: Towards Generalizable Deepfake Detection through Robust Gradient Alignment"],"prefix":"10.1109","author":[{"given":"Lingyu","family":"Qiu","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyang","family":"Tan","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICMEW46912.2020.9105991"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-8499-8_35"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00408"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/icassp.2019.8682602"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00083"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00114"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7687-1_79"},{"key":"ref8","article-title":"How does mixup help with robustness and generalization?","author":"Zhang","year":"2020"},{"key":"ref9","article-title":"Sharpness-aware minimization for efficiently improving generalization","author":"Foret","year":"2020"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00011"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01605"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.02048"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICME57554.2024.10687869"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01815"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01816"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i3.16367"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11596"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS46853.2019.9185974"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413769"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICME57554.2024.10687795"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00009"},{"key":"ref22","article-title":"The deepfake detection challenge (dfdc) preview dataset","author":"Dolhansky","year":"2019"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00327"},{"key":"ref24","article-title":"The dee pfake detection challenge (dfdc) pre view dataset","author":"Dolhansky","year":"2019"},{"key":"ref25","article-title":"Exposingaicreated fakevideos-bydetectingeyeblinking","volume-title":"2018IEEEInterG national Workshop on Information Forensics and Security (WIFS)","author":"Liy"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-5254-2"},{"key":"ref29","first-page":"4534","article-title":"Deepfakebench: a comprehensive benchmark of deepfake detection","volume-title":"Proceedings of the 37th International Conference on Neural Information Processing Systems","author":"Yan"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/WIFS.2018.8630761"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref32","first-page":"6105","article-title":"Efficientnet: Rethinking model scaling for convolutional neural networks","volume-title":"International conference on machine learning","author":"Tan"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/154"},{"key":"ref34","first-page":"5905","article-title":"Asam: Adaptive sharpness-aware minimization for scale-invariant learning of deep neural networks","volume-title":"International Conference on Machine Learning","author":"Kwon"},{"key":"ref35","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00367"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref38","first-page":"833","article-title":"Stochastic neighbor embedding","volume-title":"Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada]","author":"Hinton"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/349"}],"event":{"name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","location":"Nantes, France","start":{"date-parts":[[2025,6,30]]},"end":{"date-parts":[[2025,7,4]]}},"container-title":["2025 IEEE International Conference on Multimedia and Expo (ICME)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11208895\/11208897\/11209067.pdf?arnumber=11209067","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T05:30:32Z","timestamp":1761888632000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11209067\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/icme59968.2025.11209067","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}