{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T08:17:25Z","timestamp":1783153045333,"version":"3.54.6"},"publisher-location":"New York, NY, USA","reference-count":57,"publisher":"ACM","funder":[{"name":"the Program","award":["No. XDB0680102"],"award-info":[{"award-number":["No. XDB0680102"]}]},{"name":"National Natural Science Foundation of China","award":["No. 62472408, U25B2076 and 62441229"],"award-info":[{"award-number":["No. 62472408, U25B2076 and 62441229"]}]},{"name":"the Program","award":["No. 2023YFA1011602"],"award-info":[{"award-number":["No. 2023YFA1011602"]}]},{"name":"Tencent Joint University Collaboration Program","award":["T105-WXG-2024040800020"],"award-info":[{"award-number":["T105-WXG-2024040800020"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3774904.3792177","type":"proceedings-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T13:28:36Z","timestamp":1777296516000},"page":"1983-1992","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["D\u00e9j\u00e0 Vu of Strange Stickers! Enhancing Out-of-Distribution Robustness in Sticker Retrieval via Cross-Modal Intent Alignment"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9125-5097","authenticated-orcid":false,"given":"Yu-An","family":"Liu","sequence":"first","affiliation":[{"name":"University of Chinese Academy of Sciences, CAS, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4294-2541","authenticated-orcid":false,"given":"Ruqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, CAS, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9509-8674","authenticated-orcid":false,"given":"Jiafeng","family":"Guo","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, CAS, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0005-9465","authenticated-orcid":false,"given":"Changjiang","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, CAS, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6729-7422","authenticated-orcid":false,"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[{"name":"WeChat Search Application Department, Tencent Inc., Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1184-196X","authenticated-orcid":false,"given":"Yinhu","family":"Zhao","sequence":"additional","affiliation":[{"name":"WeChat Search Application Department, Tencent Inc., Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics9081295"},{"key":"e_1_3_2_1_2_1","volume-title":"Symbolic interactionism: Perspective and method","author":"Blumer Herbert","unstructured":"Herbert Blumer. 1986. Symbolic interactionism: Perspective and method. Univ of California Press."},{"key":"e_1_3_2_1_3_1","volume-title":"Inpars: Data augmentation for information retrieval using large language models. arXiv preprint arXiv:2202.05144","author":"Bonifacio Luiz","year":"2022","unstructured":"Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, and Rodrigo Nogueira. 2022. Inpars: Data augmentation for information retrieval using large language models. arXiv preprint arXiv:2202.05144 (2022)."},{"key":"e_1_3_2_1_4_1","volume-title":"Image-text retrieval: A survey on recent research and development. arXiv preprint arXiv:2203.14713","author":"Cao Min","year":"2022","unstructured":"Min Cao, Shiping Li, Juntao Li, Liqiang Nie, and Min Zhang. 2022. Image-text retrieval: A survey on recent research and development. arXiv preprint arXiv:2203.14713 (2022)."},{"key":"e_1_3_2_1_5_1","volume-title":"The 30th China Conference on Information Retrieval. https:\/\/www.cips-ir.org.cn\/CCIR2024\/. Accessed: 2024-10-09","author":"CCIR.","year":"2024","unstructured":"CCIR. 2024. The 30th China Conference on Information Retrieval. https:\/\/www.cips-ir.org.cn\/CCIR2024\/. Accessed: 2024-10-09."},{"key":"e_1_3_2_1_6_1","volume-title":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval. 3772-3781","author":"Metilda Chee Heng Er","year":"2025","unstructured":"Heng Er Metilda Chee, Jiayin Wang, Zhiqiang Guo, Weizhi Ma, Qinglang Guo, and Min Zhang. 2025. U-Sticker: A Large-Scale Multi-Domain User Sticker Dataset for Retrieval and Personalization. In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval. 3772-3781."},{"key":"e_1_3_2_1_7_1","first-page":"103135","article-title":"Dealing with Textual Noise for Robust and Effective BERT Re-ranking","volume":"60","author":"Chen Xuanang","year":"2023","unstructured":"Xuanang Chen, Ben He, Kai Hui, Le Sun, and Yingfei Sun. 2023. Dealing with Textual Noise for Robust and Effective BERT Re-ranking. IPM, Vol. 60 (2023), 103135.","journal-title":"IPM"},{"key":"e_1_3_2_1_8_1","first-page":"1","article-title":"Scaling instruction-finetuned language models","volume":"25","author":"Chung Hyung Won","year":"2024","unstructured":"Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al., 2024. Scaling instruction-finetuned language models. Journal of Machine Learning Research, Vol. 25, 70 (2024), 1-53.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_9_1","unstructured":"Datareportal. 2024. Digital 2024: Global Overview Report. https:\/\/datareportal.com\/reports\/digital-2024-global-overview-report Accessed: 2025-02-14."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1348246.1348248"},{"key":"e_1_3_2_1_11_1","volume-title":"International Conference on Learning Representations.","author":"Dosovitskiy Alexey","unstructured":"Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al., [n.d.]. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i16.29755"},{"key":"e_1_3_2_1_13_1","first-page":"1","article-title":"Semantic Models for the First-stage Retrieval","volume":"40","author":"Guo Jiafeng","year":"2022","unstructured":"Jiafeng Guo, Yinqiong Cai, Yixing Fan, Fei Sun, Ruqing Zhang, and Xueqi Cheng. 2022. Semantic Models for the First-stage Retrieval: A Comprehensive Review. TOIS, Vol. 40, 4 (2022), 1-42.","journal-title":"A Comprehensive Review. TOIS"},{"key":"e_1_3_2_1_14_1","volume-title":"International Conference on Learning Representations.","author":"Hendrycks Dan","year":"2017","unstructured":"Dan Hendrycks and Kevin Gimpel. 2017. A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_15_1","volume-title":"Inpars-v2: Large language models as efficient dataset generators for information retrieval. arXiv preprint arXiv:2301.01820","author":"Jeronymo Vitor","year":"2023","unstructured":"Vitor Jeronymo, Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, Roberto Lotufo, Jakub Zavrel, and Rodrigo Nogueira. 2023. Inpars-v2: Large language models as efficient dataset generators for information retrieval. arXiv preprint arXiv:2301.01820 (2023)."},{"key":"e_1_3_2_1_16_1","volume-title":"Interactive Text-to-Image Retrieval with Large Language Models: A Plug-and-Play Approach. arXiv preprint arXiv:2406.03411","author":"Lee Saehyung","year":"2024","unstructured":"Saehyung Lee, Sangwon Yu, Junsung Park, Jihun Yi, and Sungroh Yoon. 2024. Interactive Text-to-Image Retrieval with Large Language Models: A Plug-and-Play Approach. arXiv preprint arXiv:2406.03411 (2024)."},{"key":"e_1_3_2_1_17_1","volume-title":"International conference on machine learning. PMLR","author":"Li Junnan","year":"2023","unstructured":"Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023. Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. In International conference on machine learning. PMLR, 19730-19742."},{"key":"e_1_3_2_1_18_1","volume-title":"International conference on machine learning. PMLR, 12888-12900","author":"Li Junnan","year":"2022","unstructured":"Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi. 2022. Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation. In International conference on machine learning. PMLR, 12888-12900."},{"key":"e_1_3_2_1_19_1","volume-title":"Reply with Sticker: New Dataset and Model for Sticker Retrieval. arXiv preprint arXiv:2403.05427","author":"Liang Bin","year":"2024","unstructured":"Bin Liang, Bingbing Wang, Zhixin Bai, Qiwei Lang, Mingwei Sun, Kaiheng Hou, Lanjun Zhou, Ruifeng Xu, and Kam-Fai Wong. 2024. Reply with Sticker: New Dataset and Model for Sticker Retrieval. arXiv preprint arXiv:2403.05427 (2024)."},{"key":"e_1_3_2_1_20_1","unstructured":"Yu-An Liu Ruqing Zhang Jiafeng Guo Wei Chen and Xueqi Cheng. 2023. On the Robustness of Generative Retrieval Models. In Gen-IR@SIGIR."},{"key":"e_1_3_2_1_21_1","volume-title":"Robust neural information retrieval: An adversarial and out-of-distribution perspective. arXiv preprint arXiv:2407.06992","author":"Liu Yu-An","year":"2024","unstructured":"Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan, and Xueqi Cheng. 2024. Robust neural information retrieval: An adversarial and out-of-distribution perspective. arXiv preprint arXiv:2407.06992 (2024)."},{"key":"e_1_3_2_1_22_1","volume-title":"Zero-Shot Interactive Text-to-Image Retrieval via Diffusion-Augmented Representations. arXiv preprint arXiv:2501.15379","author":"Long Zijun","year":"2025","unstructured":"Zijun Long, Kangheng Liang, Gerardo Aragon-Camarasa, Richard Mccreadie, and Paul Henderson. 2025. Zero-Shot Interactive Text-to-Image Retrieval via Diffusion-Augmented Representations. arXiv preprint arXiv:2501.15379 (2025)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1561\/9781601986498"},{"key":"e_1_3_2_1_24_1","first-page":"283","article-title":"Prop","author":"Ma Xinyu","year":"2021","unstructured":"Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Xiang Ji, and Xueqi Cheng. 2021. Prop: Pre-training with Representative Words Prediction for Ad-hoc Retrieval. In WSDM. 283-291.","journal-title":"Pre-training with Representative Words Prediction for Ad-hoc Retrieval. In WSDM."},{"key":"e_1_3_2_1_25_1","first-page":"4314","article-title":"A Contrastive Pre-training Approach to Discriminative Autoencoder for Dense Retrieval","author":"Ma Xinyu","year":"2022","unstructured":"Xinyu Ma, Ruqing Zhang, Jiafeng Guo, Yixing Fan, and Xueqi Cheng. 2022. A Contrastive Pre-training Approach to Discriminative Autoencoder for Dense Retrieval. In CIKM. 4314-4318.","journal-title":"CIKM."},{"key":"e_1_3_2_1_26_1","volume-title":"PerSRV: Personalized Sticker Retrieval with Vision-Language Model. In THE WEB CONFERENCE","author":"Er Metilda Chee Heng","year":"2025","unstructured":"Chee Heng Er Metilda, Jiayin Wang, Zhiqiang Guo, Weizhi Ma, and Min Zhang. [n.d.]. PerSRV: Personalized Sticker Retrieval with Vision-Language Model. In THE WEB CONFERENCE 2025."},{"key":"e_1_3_2_1_27_1","volume-title":"MS MARCO: A Human Generated Machine Reading Comprehension Dataset. In CoCo@NIPS.","author":"Nguyen Tri","year":"2016","unstructured":"Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016. MS MARCO: A Human Generated Machine Reading Comprehension Dataset. In CoCo@NIPS."},{"key":"e_1_3_2_1_28_1","unstructured":"OpenAI. 2024. OpenAI API. https:\/\/openai.com\/api\/."},{"key":"e_1_3_2_1_29_1","first-page":"2523","article-title":"KILT: a Benchmark for Knowledge Intensive Language Tasks","author":"Petroni Fabio","year":"2021","unstructured":"Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, et al., 2021. KILT: a Benchmark for Knowledge Intensive Language Tasks. In NAACL. 2523-2544.","journal-title":"NAACL."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01361"},{"key":"e_1_3_2_1_31_1","volume-title":"International conference on machine learning. PMLR, 8748-8763","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, et al., 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748-8763."},{"key":"e_1_3_2_1_32_1","volume-title":"Language Models Are Unsupervised Multitask Learners. OpenAI blog","author":"Radford Alec","year":"2019","unstructured":"Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019. Language Models Are Unsupervised Multitask Learners. OpenAI blog, Vol. 1, 8 (2019), 9."},{"key":"e_1_3_2_1_33_1","volume-title":"Distributionally robust optimization: A review. arXiv preprint arXiv:1908.05659","author":"Rahimian Hamed","year":"2019","unstructured":"Hamed Rahimian and Sanjay Mehrotra. 2019. Distributionally robust optimization: A review. arXiv preprint arXiv:1908.05659 (2019)."},{"key":"e_1_3_2_1_34_1","volume-title":"Advances in Neural Information Processing Systems","volume":"36","author":"Ray Arijit","year":"2024","unstructured":"Arijit Ray, Filip Radenovic, Abhimanyu Dubey, Bryan Plummer, Ranjay Krishna, and Kate Saenko. 2024. Cola: A benchmark for compositional text-to-image retrieval. Advances in Neural Information Processing Systems, Vol. 36 (2024)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4471-2099-5_24"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00591"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3358995"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3060291"},{"key":"e_1_3_2_1_39_1","volume-title":"International journal of communication","author":"Tang Ying","year":"2019","unstructured":"Ying Tang and Khe Foon Hew. 2019. Emoticon, emoji, and sticker use in computer-mediated communication: A review of theories and research findings. International journal of communication, Vol. 13 (2019), 27."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-short.95"},{"key":"e_1_3_2_1_41_1","volume-title":"TENCENT ANNOUNCES 2023 THIRD QUARTER RESULTS. https:\/\/static.www.tencent.com\/uploads\/2023\/11\/15\/9e4da3187104bbdf04e2cbe491b75147","year":"2023","unstructured":"Tencent. 2023. TENCENT ANNOUNCES 2023 THIRD QUARTER RESULTS. https:\/\/static.www.tencent.com\/uploads\/2023\/11\/15\/9e4da3187104bbdf04e2cbe491b75147.pdf Accessed: 2025-02-14."},{"key":"e_1_3_2_1_42_1","volume-title":"BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models. In NIPS.","author":"Thakur Nandan","year":"2021","unstructured":"Nandan Thakur, Nils Reimers, Andreas R\u00fcckl\u00e9, Abhishek Srivastava, and Iryna Gurevych. 2021. BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models. In NIPS."},{"key":"e_1_3_2_1_43_1","volume-title":"NIPS","volume":"30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141 ukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. In NIPS, Vol. 30."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.147"},{"key":"e_1_3_2_1_45_1","volume-title":"Cross-modal retrieval: a systematic review of methods and future directions. Proc","author":"Wang Tianshi","year":"2025","unstructured":"Tianshi Wang, Fengling Li, Lei Zhu, Jingjing Li, Zheng Zhang, and Heng Tao Shen. 2025. Cross-modal retrieval: a systematic review of methods and future directions. Proc. IEEE (2025)."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00586"},{"key":"e_1_3_2_1_47_1","unstructured":"WeChat. 2024. 2024 National Information Retrieval Challenge Cup (CCIR Cup). https:\/\/algo.weixin.qq.com\/. Accessed: 2024-10-09."},{"key":"e_1_3_2_1_48_1","first-page":"24824","article-title":". Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","volume":"35","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al., 2022. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. Advances in Neural Information Processing Systems, Vol. 35 (2022), 24824-24837.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-acl.316"},{"key":"e_1_3_2_1_50_1","volume-title":"Chinese clip: Contrastive vision-language pretraining in chinese. arXiv preprint arXiv:2211.01335","author":"Yang An","year":"2022","unstructured":"An Yang, Junshu Pan, Junyang Lin, Rui Men, Yichang Zhang, Jingren Zhou, and Chang Zhou. 2022. Chinese clip: Contrastive vision-language pretraining in chinese. arXiv preprint arXiv:2211.01335 (2022)."},{"key":"e_1_3_2_1_51_1","volume-title":"COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning. arXiv preprint arXiv:2210.15212","author":"Yu Yue","year":"2022","unstructured":"Yue Yu, Chenyan Xiong, Si Sun, Chao Zhang, and Arnold Overwijk. 2022. COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning. arXiv preprint arXiv:2210.15212 (2022)."},{"key":"e_1_3_2_1_52_1","unstructured":"Aohan Zeng Xiao Liu Zhengxiao Du Zihan Wang Hanyu Lai Ming Ding Zhuoyi Yang Yifan Xu Wendi Zheng Xiao Xia et al. [n.d.]. GLM-130B: An Open Bilingual Pre-trained Model. In ICLR."},{"key":"e_1_3_2_1_53_1","volume-title":"Locating Target Regions for Image Retrieval in an Unsupervised Manner","author":"Zhang Bo-Jian","year":"2024","unstructured":"Bo-Jian Zhang, Guang-Hai Liu, Zuo-Yong Li, and Shu-Xiang Song. 2024. Locating Target Regions for Image Retrieval in an Unsupervised Manner. IEEE Transactions on Neural Networks and Learning Systems (2024)."},{"key":"e_1_3_2_1_54_1","volume-title":"Sticker820k: Empowering interactive retrieval with stickers. arXiv preprint arXiv:2306.06870","author":"Zhao Sijie","year":"2023","unstructured":"Sijie Zhao, Yixiao Ge, Zhongang Qi, Lin Song, Xiaohan Ding, Zehua Xie, and Ying Shan. 2023. Sticker820k: Empowering interactive retrieval with stickers. arXiv preprint arXiv:2306.06870 (2023)."},{"key":"e_1_3_2_1_55_1","volume-title":"Dense Text Retrieval based on Pretrained Language Models: A Survey. arXiv preprint arXiv:2211.14876","author":"Zhao Wayne Xin","year":"2022","unstructured":"Wayne Xin Zhao, Jing Liu, Ruiyang Ren, and Ji-Rong Wen. 2022. Dense Text Retrieval based on Pretrained Language Models: A Survey. arXiv preprint arXiv:2211.14876 (2022)."},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.225"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"crossref","unstructured":"Shengyao Zhuang and Guido Zuccon. 2022. CharacterBERT and Self-teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. In SIGIR.","DOI":"10.1145\/3477495.3531951"}],"event":{"name":"WWW '26: The ACM Web Conference 2026","location":"Dubai United Arab Emirates","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2026"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3774904.3792177","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T07:36:34Z","timestamp":1783150594000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774904.3792177"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":57,"alternative-id":["10.1145\/3774904.3792177","10.1145\/3774904"],"URL":"https:\/\/doi.org\/10.1145\/3774904.3792177","relation":{},"subject":[],"published":{"date-parts":[[2026,4,12]]},"assertion":[{"value":"2026-04-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}