{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T03:57:11Z","timestamp":1781150231590,"version":"3.54.1"},"reference-count":43,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neural Networks"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.neunet.2026.108926","type":"journal-article","created":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T13:10:14Z","timestamp":1775135414000},"page":"108926","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["FUGEA: Fused unified gradient ensemble for cross-architecture transferable attacks"],"prefix":"10.1016","volume":"201","author":[{"given":"Guangliang","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7814-7864","authenticated-orcid":false,"given":"Feng","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianqiang","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenhao","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runze","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neunet.2026.108926_bib0001","series-title":"International joint conference on artificial intelligence (IJCAI)","article-title":"Curriculum adversarial training","author":"Cai","year":"2018"},{"key":"10.1016\/j.neunet.2026.108926_bib0002","series-title":"Ieee\/cvf international conference on computer vision (iccv)","article-title":"An adaptive model ensemble adversarial attack for boosting adversarial transferability","author":"Chen","year":"2023"},{"key":"10.1016\/j.neunet.2026.108926_bib0003","series-title":"International conference on learning representations (ICLR)","article-title":"Rethinking model ensemble in transfer-based adversarial attacks","author":"Chen","year":"2024"},{"key":"10.1016\/j.neunet.2026.108926_bib0004","series-title":"Ieee\/cvf international conference on computer vision (iccv)","article-title":"Visformer: The vision-friendly transformer","author":"Chen","year":"2021"},{"key":"10.1016\/j.neunet.2026.108926_bib0005","series-title":"International conference on machine learning (ICML)","article-title":"Certified adversarial robustness via randomized smoothing","author":"Cohen","year":"2019"},{"key":"10.1016\/j.neunet.2026.108926_bib0006","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Boosting adversarial attacks with momentum","author":"Dong","year":"2018"},{"key":"10.1016\/j.neunet.2026.108926_bib0007","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Evading defenses to transferable adversarial examples by translation-invariant attacks","author":"Dong","year":"2019"},{"key":"10.1016\/j.neunet.2026.108926_bib0008","series-title":"International conference on learning representations (ICLR)","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2021"},{"key":"10.1016\/j.neunet.2026.108926_bib0009","series-title":"European conference on computer vision (ECCV)","article-title":"Patch-wise attack for fooling deep neural network","author":"Gao","year":"2020"},{"key":"10.1016\/j.neunet.2026.108926_bib0010","series-title":"International conference on learning representations (ICLR)","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2015"},{"key":"10.1016\/j.neunet.2026.108926_bib0011","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.neunet.2026.108926_bib0012","series-title":"Ieee\/cvf international conference on computer vision (iccv)","article-title":"Rethinking spatial dimensions of vision transformers","author":"Heo","year":"2021"},{"key":"10.1016\/j.neunet.2026.108926_bib0013","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Densely connected convolutional networks","author":"Huang","year":"2017"},{"key":"10.1016\/j.neunet.2026.108926_bib0014","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Comdefend: An efficient image compression model to defend adversarial examples","author":"Jia","year":"2019"},{"key":"10.1016\/j.neunet.2026.108926_bib0015","series-title":"European conference on computer vision (ECCV)","article-title":"Big transfer (bit): General visual representation learning","author":"Kolesnikov","year":"2020"},{"key":"10.1016\/j.neunet.2026.108926_bib0016","series-title":"International conference on learning representations (ICLR)","article-title":"Adversarial examples in the physical world","author":"Kurakin","year":"2017"},{"key":"10.1016\/j.neunet.2026.108926_bib0017","series-title":"International conference on learning representations (ICLR)","article-title":"Making substitute models more bayesian can enhance transferability of adversarial examples","author":"Li","year":"2023"},{"key":"10.1016\/j.neunet.2026.108926_bib0018","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Defense against adversarial attacks using high-level representation guided denoiser","author":"Liao","year":"2018"},{"key":"10.1016\/j.neunet.2026.108926_bib0019","series-title":"International conference on learning representations (ICLR)","article-title":"Nesterov accelerated gradient and scale invariance for adversarial attacks","author":"Lin","year":"2020"},{"key":"10.1016\/j.neunet.2026.108926_bib0020","series-title":"International conference on learning representations (ICLR)","article-title":"Delving into transferable adversarial examples and black-box attacks","author":"Liu","year":"2017"},{"key":"10.1016\/j.neunet.2026.108926_bib0021","series-title":"Ieee\/cvf international conference on computer vision (iccv)","article-title":"Swin transformer: Hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.neunet.2026.108926_bib0022","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Feature distillation: DNN-oriented JPEG compression against adversarial examples","author":"Liu","year":"2019"},{"key":"10.1016\/j.neunet.2026.108926_bib0023","series-title":"International conference on learning representations (ICLR)","article-title":"Towards deep learning models resistant to adversarial attacks","author":"Madry","year":"2018"},{"key":"10.1016\/j.neunet.2026.108926_bib0024","series-title":"Advances in neural information processing systems (neurIPS)","article-title":"Enhance the visual representation via discrete adversarial training","author":"Mao","year":"2022"},{"key":"10.1016\/j.neunet.2026.108926_bib0025","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"A self-supervised approach for adversarial robustness","author":"Naseer","year":"2020"},{"key":"10.1016\/j.neunet.2026.108926_bib0026","series-title":"International conference on machine learning (ICML)","article-title":"Diffusion models for adversarial purification","author":"Nie","year":"2022"},{"key":"10.1016\/j.neunet.2026.108926_bib0027","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Rethinking the inception architecture for computer vision","author":"Szegedy","year":"2016"},{"key":"10.1016\/j.neunet.2026.108926_bib0028","series-title":"International conference on learning representations (ICLR)","article-title":"Intriguing properties of neural networks","author":"Szegedy","year":"2014"},{"key":"10.1016\/j.neunet.2026.108926_bib0029","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Ensemble diversity facilitates adversarial transferability","author":"Tang","year":"2024"},{"key":"10.1016\/j.neunet.2026.108926_bib0030","series-title":"International conference on machine learning (ICML)","article-title":"Training data-efficient image transformers & distillation through attention","author":"Touvron","year":"2021"},{"key":"10.1016\/j.neunet.2026.108926_bib0031","series-title":"International conference on learning representations (ICLR)","article-title":"Ensemble adversarial training: Attacks and defenses","author":"Tram\u00e8r","year":"2018"},{"key":"10.1016\/j.neunet.2026.108926_bib0032","article-title":"Adversarial attack based on prediction-correction","author":"Wan","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.neunet.2026.108926_bib0033","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Boosting adversarial transferability by block shuffle and rotation","author":"Wang","year":"2024"},{"key":"10.1016\/j.neunet.2026.108926_bib0034","series-title":"Ieee\/cvf international conference on computer vision (iccv)","article-title":"Admix: Enhancing the transferability of adversarial attacks","author":"Wang","year":"2021"},{"key":"10.1016\/j.neunet.2026.108926_bib0035","series-title":"Ieee\/cvf international conference on computer vision (iccv)","article-title":"Structure invariant transformation for better adversarial transferability","author":"Wang","year":"2023"},{"key":"10.1016\/j.neunet.2026.108926_bib0036","series-title":"International conference on learning representations (ICLR)","article-title":"Fast is better than free: Revisiting adversarial training","author":"Wong","year":"2020"},{"key":"10.1016\/j.neunet.2026.108926_bib0037","series-title":"European conference on computer vision (ECCV)","article-title":"Tinyvit: Fast pretraining distillation for small vision transformers","author":"Wu","year":"2022"},{"key":"10.1016\/j.neunet.2026.108926_bib0038","series-title":"International conference on learning representations (ICLR)","article-title":"Mitigating adversarial effects through randomization","author":"Xie","year":"2018"},{"key":"10.1016\/j.neunet.2026.108926_bib0039","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Improving transferability of adversarial examples with input diversity","author":"Xie","year":"2019"},{"key":"10.1016\/j.neunet.2026.108926_bib0040","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Stochastic variance reduced ensemble adversarial attack for boosting the adversarial transferability","author":"Xiong","year":"2022"},{"key":"10.1016\/j.neunet.2026.108926_bib0041","series-title":"Ieee\/cvf international conference on computer vision (iccv)","article-title":"Meta gradient adversarial attack","author":"Yuan","year":"2021"},{"key":"10.1016\/j.neunet.2026.108926_bib0042","series-title":"Ieee\/cvf conference on computer vision and pattern recognition (cvpr)","article-title":"Improving the transferability of adversarial samples by path-augmented method","author":"Zhang","year":"2023"},{"key":"10.1016\/j.neunet.2026.108926_bib0043","series-title":"Aaai conference on artificial intelligence (aaai)","article-title":"Making adversarial examples more transferable and indistinguishable","author":"Zou","year":"2022"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026003874?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026003874?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T03:05:54Z","timestamp":1781147154000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026003874"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":43,"alternative-id":["S0893608026003874"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.108926","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"FUGEA: Fused unified gradient ensemble for cross-architecture transferable attacks","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.108926","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"108926"}}