{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T04:14:37Z","timestamp":1765340077977,"version":"3.46.0"},"publisher-location":"New York, NY, USA","reference-count":89,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"DOI":"10.1145\/3746027.3754564","type":"proceedings-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T07:38:54Z","timestamp":1761377934000},"page":"6431-6440","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Why Generate When You Can Transform? Unleashing Generative Attention for Dynamic Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8268-6792","authenticated-orcid":false,"given":"Yuli","family":"Liu","sequence":"first","affiliation":[{"name":"Quan Cheng Laboratory, Jinan, China and Qinghai University, Xining, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2247-810X","authenticated-orcid":false,"given":"Wenjun","family":"Kong","sequence":"additional","affiliation":[{"name":"School of Computer Technology and Application, Qinghai University, Xining, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5604-7527","authenticated-orcid":false,"given":"Weizhi","family":"Ma","sequence":"additional","affiliation":[{"name":"AIR, Tsinghua University, Beijing, China and Quan Cheng Laboratory, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7561-1186","authenticated-orcid":false,"given":"Cheng","family":"Luo","sequence":"additional","affiliation":[{"name":"Quan Cheng Laboratory, Jinan, China and MegaTech.AI, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313568"},{"key":"e_1_3_2_1_2_1","volume-title":"A survey of sequential recommendation systems: Techniques, evaluation, and future directions. Information Systems","author":"Boka Tesfaye Fenta","year":"2024","unstructured":"Tesfaye Fenta Boka, Zhendong Niu, and Rama Bastola Neupane. 2024. A survey of sequential recommendation systems: Techniques, evaluation, and future directions. Information Systems (2024), 102427."},{"key":"e_1_3_2_1_3_1","volume-title":"Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models","author":"Bond-Taylor Sam","year":"2021","unstructured":"Sam Bond-Taylor, Adam Leach, Yang Long, and Chris G Willcocks. 2021. Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models. IEEE transactions on pattern analysis and machine intelligence 44, 11 (2021), 7327-7347."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/204"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3050407"},{"key":"e_1_3_2_1_6_1","first-page":"1","article-title":"DualCFGL: dual-channel fusion global and local features for sequential recommendation","volume":"11","author":"Chen Shuxu","year":"2025","unstructured":"Shuxu Chen, Yuanyuan Liu, Chao Che, Ziqi Wei, and Zhaoqian Zhong. 2025. DualCFGL: dual-channel fusion global and local features for sequential recommendation. Complex & Intelligent Systems 11, 1 (2025), 1-18.","journal-title":"Complex & Intelligent Systems"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531894"},{"key":"e_1_3_2_1_8_1","volume-title":"Sequential recommendation via agent-based irrelevancy skipping. Neural Networks","author":"Cheng Yu","year":"2025","unstructured":"Yu Cheng, Jiawei Zheng, Binquan Wu, and Qianli Ma. 2025. Sequential recommendation via agent-based irrelevancy skipping. Neural Networks (2025), 107134."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25883"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2881260"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671474"},{"key":"e_1_3_2_1_12_1","volume-title":"Sequential recommendation with diffusion models. arXiv preprint arXiv:2304.04541","author":"Du Hanwen","year":"2023","unstructured":"Hanwen Du, Huanhuan Yuan, Zhen Huang, Pengpeng Zhao, and Xiaofang Zhou. 2023. Sequential recommendation with diffusion models. arXiv preprint arXiv:2304.04541 (2023)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570373"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591689"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2004.09.018"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512077"},{"key":"e_1_3_2_1_17_1","volume-title":"Attention in natural language processing","author":"Galassi Andrea","year":"2020","unstructured":"Andrea Galassi, Marco Lippi, and Paolo Torroni. 2020. Attention in natural language processing. IEEE transactions on neural networks and learning systems 32, 10 (2020), 4291-4308."},{"key":"e_1_3_2_1_18_1","volume-title":"Personalized Dual Transformer Network for sequential recommendation. Neurocomputing","author":"Ge Meiling","year":"2025","unstructured":"Meiling Ge, Chengduan Wang, Xueyang Qin, Jiangyan Dai, Lei Huang, Qibing Qin, and Wenfeng Zhang. 2025. Personalized Dual Transformer Network for sequential recommendation. Neurocomputing (2025), 129244."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-24797-2"},{"key":"e_1_3_2_1_20_1","volume-title":"Attention mechanisms in computer vision: A survey. Computational visual media 8, 3","author":"Guo Meng-Hao","year":"2022","unstructured":"Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu, Zheng-Ning Liu, Peng-Tao Jiang, Tai-Jiang Mu, Song-Hai Zhang, Ralph R Martin, Ming-Ming Cheng, and Shi-Min Hu. 2022. Attention mechanisms in computer vision: A survey. Computational visual media 8, 3 (2022), 331-368."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645380"},{"key":"e_1_3_2_1_22_1","volume-title":"The movielens datasets: History and context. Acm transactions on interactive intelligent systems (tiis) 5, 4","author":"Maxwell Harper F","year":"2015","unstructured":"F Maxwell Harper and Joseph A Konstan. 2015. The movielens datasets: History and context. Acm transactions on interactive intelligent systems (tiis) 5, 4 (2015), 1-19."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0030"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883037"},{"key":"e_1_3_2_1_25_1","volume-title":"Denoising diffusion probabilistic models. Advances in neural information processing systems 33","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. Advances in neural information processing systems 33 (2020), 6840- 6851."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240609"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681498"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3616855.3635850"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128932"},{"key":"e_1_3_2_1_31_1","volume-title":"Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114","author":"Kingma Diederik P","year":"2013","unstructured":"Diederik P Kingma. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608779"},{"key":"e_1_3_2_1_33_1","volume-title":"DGT: Unbiased sequential recommendation via Disentangled Graph Transformer. Knowledge-Based Systems","author":"Li Chenglin","year":"2025","unstructured":"Chenglin Li, Tao Xie, Chenyun Yu, Bo Hu, Zang Li, Lei Cheng, Beibei Kong, and Di Niu. 2025. DGT: Unbiased sequential recommendation via Disentangled Graph Transformer. Knowledge-Based Systems (2025), 112946."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371786"},{"key":"e_1_3_2_1_35_1","first-page":"1","article-title":"Diffurec: A diffusion model for sequential recommendation","volume":"42","author":"Li Zihao","year":"2023","unstructured":"Zihao Li, Aixin Sun, and Chenliang Li. 2023. Diffurec: A diffusion model for sequential recommendation. ACM Transactions on Information Systems 42, 3 (2023), 1-28.","journal-title":"ACM Transactions on Information Systems"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186150"},{"key":"e_1_3_2_1_37_1","volume-title":"International Conference on Learning Representations.","author":"Lin Zhouhan","year":"2022","unstructured":"Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, and Yoshua Bengio. 2022. A STRUCTURED SELFATTENTIVE SENTENCE EMBEDDING. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_38_1","volume-title":"MMGRec: Multimodal Generative Recommendation with Transformer Model. arXiv preprint arXiv:2404.16555","author":"Liu Han","year":"2024","unstructured":"Han Liu, Yinwei Wei, Xuemeng Song, Weili Guan, Yuan-Fang Li, and Liqiang Nie. 2024. MMGRec: Multimodal Generative Recommendation with Transformer Model. arXiv preprint arXiv:2404.16555 (2024)."},{"key":"e_1_3_2_1_39_1","volume-title":"2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, 1053-1058","author":"Liu Qiang","year":"2016","unstructured":"Qiang Liu, Shu Wu, Diyi Wang, Zhaokang Li, and Liang Wang. 2016. Contextaware sequential recommendation. In 2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, 1053-1058."},{"key":"e_1_3_2_1_40_1","volume-title":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 1524-1534","author":"Liu Shuchang","year":"2023","unstructured":"Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian McAuley, Dong Zheng, Peng Jiang, and Kun Gai. 2023. Generative flownetwork for listwise recommendation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 1524-1534."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2024.102488"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3640457.3688164"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671733"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657716"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-022-01711-7"},{"key":"e_1_3_2_1_46_1","volume-title":"Pone-GNN: Integrating Positive and Negative Feedback in Graph Neural Networks for Recommender Systems. ACM Transactions on Recommender Systems","author":"Liu Ziyang","year":"2025","unstructured":"Ziyang Liu, Chaokun Wang, Shuwen Zheng, Cheng Wu, Kai Zheng, Yang Song, and Na Mou. 2025. Pone-GNN: Integrating Positive and Negative Feedback in Graph Neural Networks for Recommender Systems. ACM Transactions on Recommender Systems (2025)."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-73200-4_2"},{"key":"e_1_3_2_1_48_1","volume-title":"A universal approximation theorem of deep neural networks for expressing probability distributions. Advances in neural information processing systems 33","author":"Lu Yulong","year":"2020","unstructured":"Yulong Lu and Jianfeng Lu. 2020. A universal approximation theorem of deep neural networks for expressing probability distributions. Advances in neural information processing systems 33 (2020), 3094-3105."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28736"},{"key":"e_1_3_2_1_50_1","volume-title":"Sylvain Le Corff, and Olivier Pietquin","author":"Martin Alice","year":"2020","unstructured":"Alice Martin, Charles Ollion, Florian Strub, Sylvain Le Corff, and Olivier Pietquin. 2020. The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction. arXiv preprint arXiv:2007.08620 (2020)."},{"key":"e_1_3_2_1_51_1","volume-title":"The shaped transformer: Attention models in the infinite depth-and-width limit. Advances in Neural Information Processing Systems 36","author":"Noci Lorenzo","year":"2024","unstructured":"Lorenzo Noci, Chuning Li, Mufan Li, Bobby He, Thomas Hofmann, Chris J Maddison, and Dan Roy. 2024. The shaped transformer: Attention models in the infinite depth-and-width limit. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959149"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3616855.3635773"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498433"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3546777"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401111"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371831"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16564"},{"key":"e_1_3_2_1_60_1","first-page":"23592","article-title":"Probabilistic transformer for time series analysis","volume":"34","author":"Tang Binh","year":"2021","unstructured":"Binh Tang and David S Matteson. 2021. Probabilistic transformer for time series analysis. Advances in Neural Information Processing Systems 34 (2021), 23592-23608.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657805"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591951"},{"key":"e_1_3_2_1_64_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3522673"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080786"},{"key":"e_1_3_2_1_67_1","volume-title":"International Conference on Machine Learning. PMLR, 36246-36263","author":"Wang Zekai","year":"2023","unstructured":"Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, and Shuicheng Yan. 2023. Better diffusion models further improve adversarial training. In International Conference on Machine Learning. PMLR, 36246-36263."},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331214"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/537"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00099"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449873"},{"key":"e_1_3_2_1_72_1","first-page":"3940","volume-title":"IJCAI","volume":"19","author":"Xu Chengfeng","year":"2019","unstructured":"Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Victor S Sheng, Jiajie Xu, Fuzhen Zhuang, Junhua Fang, and Xiaofang Zhou. 2019. Graph contextualized selfattention network for session-based recommendation.. In IJCAI, Vol. 19. 3940-3946."},{"key":"e_1_3_2_1_73_1","volume-title":"Zhiming Cui, Xiaofang Zhou, and Hui Xiong.","author":"Xu Chengfeng","year":"2019","unstructured":"Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Jiajie Xu, Victor S Sheng S. Sheng, Zhiming Cui, Xiaofang Zhou, and Hui Xiong. 2019. Recurrent convolutional neural network for sequential recommendation. In The world wide web conference. 3398-3404."},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2023.11.039"},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358113"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"crossref","unstructured":"Haochao Ying Fuzhen Zhuang Fuzheng Zhang Yanchi Liu Guandong Xu Xing Xie Hui Xiong and Jian Wu. 2018. Sequential recommender system based on hierarchical attention network. In IJCAI international joint conference on artificial intelligence.","DOI":"10.24963\/ijcai.2018\/546"},{"key":"e_1_3_2_1_77_1","volume-title":"Semi-supervised learning with deep generative models for asset failure prediction. arXiv preprint arXiv:1709.00845","author":"Yoon Andre S","year":"2017","unstructured":"Andre S Yoon, Taehoon Lee, Yongsub Lim, Deokwoo Jung, Philgyun Kang, Dongwon Kim, Keuntae Park, and Yongjin Choi. 2017. Semi-supervised learning with deep generative models for asset failure prediction. arXiv preprint arXiv:1709.00845 (2017)."},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512064"},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.09.007"},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1145\/1454008.1454030"},{"key":"e_1_3_2_1_81_1","first-page":"4741","article-title":"Dynamic graph neural networks for sequential recommendation","volume":"35","author":"Zhang Mengqi","year":"2022","unstructured":"Mengqi Zhang, Shu Wu, Xueli Yu, Qiang Liu, and Liang Wang. 2022. Dynamic graph neural networks for sequential recommendation. IEEE Transactions on Knowledge and Data Engineering 35, 5 (2022), 4741-4753.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_82_1","first-page":"4320","article-title":"Feature-level deeper selfattention network for sequential recommendation","author":"Zhang Tingting","year":"2019","unstructured":"Tingting Zhang, Pengpeng Zhao, Yanchi Liu, Victor S Sheng, Jiajie Xu, Deqing Wang, Guanfeng Liu, Xiaofang Zhou, et al. 2019. Feature-level deeper selfattention network for sequential recommendation.. In IJCAI. 4320-4326.","journal-title":"IJCAI."},{"key":"e_1_3_2_1_83_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657825"},{"key":"e_1_3_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00138"},{"key":"e_1_3_2_1_85_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2980517"},{"key":"e_1_3_2_1_86_1","volume-title":"On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers. In International Conference on Artificial Intelligence and Statistics. PMLR, 2179-2187","author":"Zhou Cai","year":"2024","unstructured":"Cai Zhou, Rose Yu, and Yusu Wang. 2024. On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers. In International Conference on Artificial Intelligence and Statistics. PMLR, 2179-2187."},{"key":"e_1_3_2_1_87_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2020.2994780"},{"key":"e_1_3_2_1_88_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657816"},{"key":"e_1_3_2_1_89_1","volume-title":"Generative Diffusion Models for Sequential Recommendations. arXiv preprint arXiv:2410.19429","author":"Zolghadr Sharare","year":"2024","unstructured":"Sharare Zolghadr, Ole Winther, and Paul Jeha. 2024. Generative Diffusion Models for Sequential Recommendations. arXiv preprint arXiv:2410.19429 (2024)."}],"event":{"name":"MM '25: The 33rd ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Dublin Ireland","acronym":"MM '25"},"container-title":["Proceedings of the 33rd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746027.3754564","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T04:10:34Z","timestamp":1765339834000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746027.3754564"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":89,"alternative-id":["10.1145\/3746027.3754564","10.1145\/3746027"],"URL":"https:\/\/doi.org\/10.1145\/3746027.3754564","relation":{},"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"2025-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}