{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:31:25Z","timestamp":1765499485238,"version":"3.48.0"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62002303, 42171456"],"award-info":[{"award-number":["62002303, 42171456"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Xiamen, China","award":["3502Z202471028"],"award-info":[{"award-number":["3502Z202471028"]}]},{"name":"Guangdong Basic and Applied Basic Research Foundation","award":["2023A1515012848"],"award-info":[{"award-number":["2023A1515012848"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,10]]},"DOI":"10.1145\/3746252.3761034","type":"proceedings-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T23:59:18Z","timestamp":1762559958000},"page":"1829-1838","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["SC-DAG: Semantic-Constrained Diffusion Attacks for Stealthy Exposure Manipulation in Visually-Aware Recommender Systems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-3078-9270","authenticated-orcid":false,"given":"Ze","family":"Lin","sequence":"first","affiliation":[{"name":"Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, Xiamen, Fujian, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8894-3271","authenticated-orcid":false,"given":"Yuqiu","family":"Qian","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5985-9886","authenticated-orcid":false,"given":"Xiaodong","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, Xiamen, Fujian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3049-0085","authenticated-orcid":false,"given":"Ziyu","family":"Lyu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Sun Yat-sen University, Shenzhen, Guangdong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9139-3855","authenticated-orcid":false,"given":"Hui","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, Xiamen, Fujian, China"}]}],"member":"320","published-online":{"date-parts":[[2025,11,10]]},"reference":[{"key":"e_1_3_2_2_1_1","first-page":"577","article-title":"Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems","author":"Burke Robin D.","year":"2005","unstructured":"Robin D. Burke, Bamshad Mobasher, Runa Bhaumik, and Chad Williams. 2005. Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems. In ICDM. 577-580.","journal-title":"ICDM."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3361474"},{"key":"e_1_3_2_2_3_1","first-page":"335","article-title":"Attentive Collaborative Filtering","author":"Chen Jingyuan","year":"2017","unstructured":"Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, and Tat- Seng Chua. 2017. Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention. In SIGIR. 335-344.","journal-title":"Multimedia Recommendation with Item- and Component-Level Attention. In SIGIR."},{"key":"e_1_3_2_2_4_1","volume-title":"Rethinking Atrous Convolution for Semantic Image Segmentation. arXiv Preprint","author":"Chen Liang-Chieh","year":"2017","unstructured":"Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam. 2017. Rethinking Atrous Convolution for Semantic Image Segmentation. arXiv Preprint (2017). http:\/\/arxiv.org\/abs\/1706.05587"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3666088"},{"key":"e_1_3_2_2_6_1","first-page":"322","article-title":"Adversarial attacks on an oblivious recommender","author":"Christakopoulou Konstantina","year":"2019","unstructured":"Konstantina Christakopoulou and Arindam Banerjee. 2019. Adversarial attacks on an oblivious recommender. In RecSys. 322-330.","journal-title":"RecSys."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441757"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3261988"},{"key":"e_1_3_2_2_9_1","first-page":"1583","article-title":"Attacking Black-box Recommendations via Copying Cross-domain User Profiles","author":"Fan Wenqi","year":"2021","unstructured":"Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, and Qing Li. 2021. Attacking Black-box Recommendations via Copying Cross-domain User Profiles. In ICDE. 1583-1594.","journal-title":"ICDE."},{"key":"e_1_3_2_2_10_1","unstructured":"Ian J. Goodfellow Jonathon Shlens and Christian Szegedy. 2015. Explaining and Harnessing Adversarial Examples. arXiv Preprint. https:\/\/arxiv.org\/abs\/1412.6572"},{"key":"e_1_3_2_2_11_1","volume-title":"McAuley","author":"He Ruining","year":"2016","unstructured":"Ruining He and Julian J. McAuley. 2016. VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback. In AAAI. 144-150."},{"key":"e_1_3_2_2_12_1","first-page":"1","article-title":"Iterative \u03b1 - (de)Blending: a Minimalist Deterministic Diffusion Model","volume":"34","author":"Heitz Eric","year":"2023","unstructured":"Eric Heitz, Laurent Belcour, and Thomas Chambon. 2023. Iterative \u03b1 - (de)Blending: a Minimalist Deterministic Diffusion Model. In SIGGRAPH. 34:1- 34:8.","journal-title":"SIGGRAPH."},{"key":"e_1_3_2_2_13_1","first-page":"6626","article-title":"GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium","author":"Heusel Martin","year":"2017","unstructured":"Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter. 2017. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. In NeurIPS. 6626-6637.","journal-title":"NeurIPS."},{"key":"e_1_3_2_2_14_1","first-page":"6840","article-title":"Denoising Diffusion Probabilistic Models","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising Diffusion Probabilistic Models. In NeurIPS. 6840-685.","journal-title":"NeurIPS."},{"key":"e_1_3_2_2_15_1","first-page":"864","article-title":"Single-User Injection for Invisible Shilling Attack against Recommender Systems","author":"Huang Chengzhi","year":"2023","unstructured":"Chengzhi Huang and Hui Li. 2023. Single-User Injection for Invisible Shilling Attack against Recommender Systems. In CIKM. 864-873.","journal-title":"CIKM."},{"key":"e_1_3_2_2_16_1","first-page":"22863","article-title":"A Variational Perspective on Diffusion-Based Generative Models and Score Matching","author":"Huang Chin-Wei","year":"2021","unstructured":"Chin-Wei Huang, Jae Hyun Lim, and Aaron C. Courville. 2021. A Variational Perspective on Diffusion-Based Generative Models and Score Matching. In NeurIPS. 22863-22876.","journal-title":"NeurIPS."},{"key":"e_1_3_2_2_17_1","first-page":"105","article-title":"Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos","author":"Kalantidis Yannis","year":"2013","unstructured":"Yannis Kalantidis, Lyndon Kennedy, and Li-Jia Li. 2013. Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos. In ICMR. 105-112.","journal-title":"ICMR."},{"key":"e_1_3_2_2_18_1","first-page":"207","article-title":"Visually-Aware Fashion Recommendation and Design with Generative Image Models","author":"Kang Wang-Cheng","year":"2017","unstructured":"Wang-Cheng Kang, Chen Fang, Zhaowen Wang, and Julian J. McAuley. 2017. Visually-Aware Fashion Recommendation and Design with Generative Image Models. In ICDM. 207-216.","journal-title":"ICDM."},{"key":"e_1_3_2_2_19_1","volume-title":"Variational Diffusion Models. arXiv Preprint","author":"Kingma Diederik P.","year":"2021","unstructured":"Diederik P. Kingma, Tim Salimans, Ben Poole, and Jonathan Ho. 2021. Variational Diffusion Models. arXiv Preprint (2021). https:\/\/arxiv.org\/abs\/2107.00630"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/988672.988726"},{"key":"e_1_3_2_2_22_1","first-page":"855","article-title":"Attacking Recommender Systems with Augmented User Profiles","author":"Lin Chen","year":"2020","unstructured":"Chen Lin, Si Chen, Hui Li, Yanghua Xiao, Lianyun Li, and Qian Yang. 2020. Attacking Recommender Systems with Augmented User Profiles. In CIKM. 855-864.","journal-title":"CIKM."},{"key":"e_1_3_2_2_23_1","volume-title":"Multimodal Recommender Systems: A Survey. ACM Comput. Surv. 57, 2","author":"Liu Qidong","year":"2025","unstructured":"Qidong Liu, Jiaxi Hu, Yutian Xiao, Xiangyu Zhao, Jingtong Gao, Wanyu Wang, Qing Li, and Jiliang Tang. 2025. Multimodal Recommender Systems: A Survey. ACM Comput. Surv. 57, 2 (2025), 26:1-26:17."},{"key":"e_1_3_2_2_24_1","unstructured":"Xingchao Liu Chengyue Gong and Qiang Liu. 2023. Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. In ICLR."},{"key":"e_1_3_2_2_25_1","first-page":"3590","article-title":"Adversarial Item Promotion: Vulnerabilities at the Core of Top-N Recommenders that Use Images to Address Cold Start","author":"Liu Zhuoran","year":"2021","unstructured":"Zhuoran Liu and Martha A. Larson. 2021. Adversarial Item Promotion: Vulnerabilities at the Core of Top-N Recommenders that Use Images to Address Cold Start. In WWW. 3590-3602.","journal-title":"WWW."},{"key":"e_1_3_2_2_26_1","volume-title":"Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed. arXiv Preprint","author":"Luhman Eric","year":"2021","unstructured":"Eric Luhman and Troy Luhman. 2021. Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed. arXiv Preprint (2021). https:\/\/arxiv.org\/abs\/2101.02388"},{"key":"e_1_3_2_2_27_1","first-page":"8162","volume-title":"ICML","volume":"139","author":"Nichol Alexander Quinn","year":"2021","unstructured":"Alexander Quinn Nichol and Prafulla Dhariwal. 2021. Improved Denoising Diffusion Probabilistic Models. In ICML, Vol. 139. 8162-8171."},{"key":"e_1_3_2_2_28_1","first-page":"1","article-title":"TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems","author":"Noia Tommaso Di","year":"2020","unstructured":"Tommaso Di Noia, Daniele Malitesta, and Felice Antonio Merra. 2020. TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems. In DSN. 1-8.","journal-title":"DSN."},{"key":"e_1_3_2_2_29_1","volume-title":"Silvestre","author":"O'Mahony Michael P.","year":"2005","unstructured":"Michael P. O'Mahony, Neil J. Hurley, and Guenole C. M. Silvestre. 2005. Recommender Systems: Attack Types and Strategies. In AAAI. 334-339."},{"key":"e_1_3_2_2_30_1","first-page":"8748","volume-title":"ICML","volume":"139","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021. Learning Transferable Visual Models From Natural Language Supervision. In ICML, Vol. 139. 8748-8763."},{"key":"e_1_3_2_2_31_1","first-page":"452","article-title":"BPR: Bayesian Personalized Ranking from Implicit Feedback","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI. 452-461.","journal-title":"UAI."},{"key":"e_1_3_2_2_32_1","first-page":"10674","article-title":"High-Resolution Image Synthesis with Latent Diffusion Models","author":"Rombach Robin","year":"2022","unstructured":"Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Bj\u00f6rn Ommer. 2022. High-Resolution Image Synthesis with Latent Diffusion Models. In CVPR. 10674-10685.","journal-title":"CVPR."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-018-9655-x"},{"key":"e_1_3_2_2_34_1","first-page":"1415","article-title":"Maximum Likelihood Training of Score-Based Diffusion Models","author":"Song Yang","year":"2021","unstructured":"Yang Song, Conor Durkan, Iain Murray, and Stefano Ermon. 2021. Maximum Likelihood Training of Score-Based Diffusion Models. In NeurIPS. 1415-1428.","journal-title":"NeurIPS."},{"key":"e_1_3_2_2_35_1","unstructured":"Yang Song Jascha Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon and Ben Poole. 2021. Score-Based Generative Modeling through Stochastic Differential Equations. In ICLR."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2893638"},{"key":"e_1_3_2_2_37_1","first-page":"1830","article-title":"Triple Adversarial Learning for Influence based Poisoning Attack in Recommender Systems","author":"Wu Chenwang","year":"2021","unstructured":"Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, and Enhong Chen. 2021. Triple Adversarial Learning for Influence based Poisoning Attack in Recommender Systems. In KDD. 1830-1840.","journal-title":"KDD."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3274759"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3145690"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2209.00796"},{"key":"e_1_3_2_2_41_1","first-page":"2900","article-title":"Attacking Visually-aware Recommender Systems with Transferable and Imperceptible Adversarial Styles","author":"Yang Shiyi","year":"2024","unstructured":"Shiyi Yang, Chen Wang, Xiwei Xu, Liming Zhu, and Lina Yao. 2024. Attacking Visually-aware Recommender Systems with Transferable and Imperceptible Adversarial Styles. In CIKM. 2900-2909.","journal-title":"CIKM."},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25612"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3181270"},{"key":"e_1_3_2_2_44_1","volume-title":"Deep Learning based Recommender System: A Survey and New Perspectives. arXiv Preprint","author":"Zhang Shuai","year":"2017","unstructured":"Shuai Zhang, Lina Yao, and Aixin Sun. 2017. Deep Learning based Recommender System: A Survey and New Perspectives. arXiv Preprint (2017). http:\/\/arxiv.org\/abs\/1707.07435"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3392335"}],"event":{"name":"CIKM '25: The 34th ACM International Conference on Information and Knowledge Management","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Seoul Republic of Korea","acronym":"CIKM '25"},"container-title":["Proceedings of the 34th ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746252.3761034","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:26:31Z","timestamp":1765499191000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746252.3761034"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,10]]},"references-count":45,"alternative-id":["10.1145\/3746252.3761034","10.1145\/3746252"],"URL":"https:\/\/doi.org\/10.1145\/3746252.3761034","relation":{},"subject":[],"published":{"date-parts":[[2025,11,10]]},"assertion":[{"value":"2025-11-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}