{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T17:17:17Z","timestamp":1775841437031,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3774904.3792706","type":"proceedings-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T21:54:39Z","timestamp":1775771679000},"page":"1841-1851","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Navigating Truth in Multimodal Fact-checking via Retrieval- and Reasoning-Enhanced Large Language Models"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1078-430X","authenticated-orcid":false,"given":"Fanrui","family":"Zhang","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, hefei, China and Shanghai Innovation Institute, shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7809-5818","authenticated-orcid":false,"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3145-5225","authenticated-orcid":false,"given":"Jianwen","family":"Sun","sequence":"additional","affiliation":[{"name":"Nankai University, tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5769-3739","authenticated-orcid":false,"given":"Chuanhao","family":"Li","sequence":"additional","affiliation":[{"name":"Shanghai AI Laboratory, shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4303-7749","authenticated-orcid":false,"given":"Jiaxin","family":"Ai","sequence":"additional","affiliation":[{"name":"Wuhan University, wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5594-3629","authenticated-orcid":false,"given":"Yukang","family":"Feng","sequence":"additional","affiliation":[{"name":"Nankai University, tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6554-9734","authenticated-orcid":false,"given":"Zizhen","family":"Li","sequence":"additional","affiliation":[{"name":"Nankai University, tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6105-6532","authenticated-orcid":false,"given":"Kaipeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Innovation Institute, shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9940-6366","authenticated-orcid":false,"given":"Jiawei","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2510-8993","authenticated-orcid":false,"given":"Zheng-Jun","family":"Zha","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,4,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01452"},{"key":"e_1_3_2_1_2_1","volume-title":"Dbpedia: A nucleus for a web of open data. In international semantic web conference","author":"Auer S\u00f6ren","year":"2007","unstructured":"S\u00f6ren Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2007. Dbpedia: A nucleus for a web of open data. In international semantic web conference. Springer, 722-735."},{"key":"e_1_3_2_1_3_1","volume-title":"Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond. arXiv preprint arXiv:2308.12966","author":"Bai Jinze","year":"2023","unstructured":"Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou. 2023. Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond. arXiv preprint arXiv:2308.12966, Vol. 1, 2 (2023), 3."},{"key":"e_1_3_2_1_4_1","volume-title":"arXiv preprint arXiv:2502.13923","author":"Bai Shuai","year":"2025","unstructured":"Shuai Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Sibo Song, Kai Dang, Peng Wang, Shijie Wang, Jun Tang, Humen Zhong, Yuanzhi Zhu, Mingkun Yang, Zhaohai Li, Jianqiang Wan, Pengfei Wang, Wei Ding, Zheren Fu, Yiheng Xu, Jiabo Ye, Xi Zhang, Tianbao Xie, Zesen Cheng, Hang Zhang, Zhibo Yang, Haiyang Xu, and Junyang Lin. 2025. Qwen2.5-VL Technical Report. arXiv preprint arXiv:2502.13923 (2025)."},{"key":"e_1_3_2_1_5_1","volume-title":"Proceedings of the 42nd International Conference on Machine Learning. https:\/\/arxiv.org\/abs\/2412","author":"Braun Tobias","year":"2025","unstructured":"Tobias Braun, Mark Rothermel, Marcus Rohrbach, and Anna Rohrbach. 2025. DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts. In Proceedings of the 42nd International Conference on Machine Learning. https:\/\/arxiv.org\/abs\/2412.10510"},{"key":"e_1_3_2_1_6_1","volume-title":"Multi-source Knowledge Enhanced Graph Attention Networks for Multimodal Fact Verification. In 2024 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 1-6.","author":"Cao Han","year":"2024","unstructured":"Han Cao, Lingwei Wei, Wei Zhou, and Songlin Hu. 2024. Multi-source Knowledge Enhanced Graph Attention Networks for Multimodal Fact Verification. In 2024 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 1-6."},{"key":"e_1_3_2_1_7_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 24185-24198","author":"Chen Zhe","year":"2024","unstructured":"Zhe Chen, Jiannan Wu, Wenhai Wang, Weijie Su, Guo Chen, Sen Xing, Muyan Zhong, Qinglong Zhang, Xizhou Zhu, Lewei Lu, et al., 2024. Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 24185-24198."},{"key":"e_1_3_2_1_8_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_9_1","first-page":"4171","volume-title":"Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies","volume":"1","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers). 4171-4186."},{"key":"e_1_3_2_1_10_1","unstructured":"Abhishek Dhankar Osmar R. Za\u00efane and Francois Bolduc. 2022. UofA-Truth at Factify 2022 : Transformer And Transfer Learning Based Multi-Modal Fact-Checking. arXiv:2203.07990 [cs.MM]"},{"key":"e_1_3_2_1_11_1","volume-title":"Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation Models with Feature Representations for Multi-Modal Fact Verification. arXiv preprint arXiv:2302","author":"Du Wei-Wei","year":"2023","unstructured":"Wei-Wei Du, Hong-Wei Wu, Wei-Yao Wang, and Wen-Chih Peng. 2023. Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation Models with Feature Representations for Multi-Modal Fact Verification. arXiv preprint arXiv:2302 (2023)."},{"key":"e_1_3_2_1_12_1","volume-title":"Logically at Factify 2022: Multimodal Fact Verfication. ArXiv","author":"Gao Jie","year":"2021","unstructured":"Jie Gao, Hella-Franziska Hoffmann, Stylianos Oikonomou, David Kiskovski, and Anil Bandhakavi. 2021. Logically at Factify 2022: Multimodal Fact Verfication. ArXiv, Vol. abs\/2112.09253 (2021)."},{"key":"e_1_3_2_1_13_1","unstructured":"Daya Guo Dejian Yang Haowei Zhang Junxiao Song Ruoyu Zhang Runxin Xu Qihao Zhu Shirong Ma Peiyi Wang Xiao Bi et al. 2025. Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning. arXiv preprint arXiv:2501.12948 (2025)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00454"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591896"},{"key":"e_1_3_2_1_16_1","unstructured":"Aaron Jaech Adam Kalai Adam Lerer Adam Richardson Ahmed El-Kishky Aiden Low Alec Helyar Aleksander Madry Alex Beutel Alex Carney et al. 2024. Openai o1 system card. arXiv preprint arXiv:2412.16720 (2024)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123385"},{"key":"e_1_3_2_1_18_1","volume-title":"Manish Gupta, and Vasudeva Varma.","author":"Khattar Dhruv","year":"2019","unstructured":"Dhruv Khattar, Jaipal Singh Goud, Manish Gupta, and Vasudeva Varma. 2019. Mvae: Multimodal variational autoencoder for fake news detection. In The world wide web conference. 2915-2921."},{"key":"e_1_3_2_1_19_1","volume-title":"International Conference on Machine Learning (Proceedings of Machine Learning Research","volume":"19742","author":"Li Junnan","unstructured":"Junnan Li, Dongxu Li, Silvio Savarese, and Steven C. H. Hoi. 2023. BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models. In International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 202), Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). 19730-19742."},{"key":"e_1_3_2_1_20_1","unstructured":"Fuxiao Liu Yinghan Wang Tianlu Wang and Vicente Ordonez. 2020. VisualNews : Benchmark and Challenges in Entity-aware Image Captioning. arXiv:2010.03743 [cs.CV]"},{"key":"e_1_3_2_1_21_1","unstructured":"Haotian Liu Chunyuan Li Qingyang Wu and Yong Jae Lee. 2023. Visual Instruction Tuning. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_22_1","volume-title":"Newsclippings: Automatic generation of out-of-context multimodal media. arXiv preprint arXiv:2104.05893","author":"Luo Grace","year":"2021","unstructured":"Grace Luo, Trevor Darrell, and Anna Rohrbach. 2021. Newsclippings: Automatic generation of out-of-context multimodal media. arXiv preprint arXiv:2104.05893 (2021)."},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings of the First Workshop on Multimodal Fact-Checking and Hate Speech Detection (DE-FACTIFY).","author":"Mishra Shreyash","year":"2022","unstructured":"Shreyash Mishra, S Suryavardan, Amrit Bhaskar, Parul Chopra, Aishwarya Reganti, Parth Patwa, Amitava Das, Tanmoy Chakraborty, Amit Sheth, Asif Ekbal, et al., 2022. Factify: A multi-modal fact verification dataset. In Proceedings of the First Workshop on Multimodal Fact-Checking and Hate Speech Detection (DE-FACTIFY)."},{"key":"e_1_3_2_1_24_1","unstructured":"OpenAI. 2023. GPT-4V(ision) System Card. https:\/\/cdn.openai.com\/papers\/GPTV_System_Card.pdf."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13735-023-00312-6"},{"key":"e_1_3_2_1_26_1","volume-title":"Red-dot: Multimodal fact-checking via relevant evidence detection","author":"Papadopoulos Stefanos-Iordanis","year":"2025","unstructured":"Stefanos-Iordanis Papadopoulos, Christos Koutlis, Symeon Papadopoulos, and Panagiotis C Petrantonakis. 2025a. Red-dot: Multimodal fact-checking via relevant evidence detection. IEEE Transactions on Computational Social Systems (2025)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV61041.2025.00544"},{"key":"e_1_3_2_1_28_1","unstructured":"Parth Patwa Shreyash Mishra S Suryavardan Amrit Bhaskar Parul Chopra Aishwarya N. Reganti Amitava Das Tanmoy Chakraborty A. Sheth Asif Ekbal and Chaitanya Ahuja. 2022. Benchmarking Multi-Modal Entailment for Fact Verification (short paper). In DE-FACTIFY@AAAI."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01240"},{"key":"e_1_3_2_1_30_1","volume-title":"Proceedings of the 38th International Conference on Machine Learning, 2021","volume":"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, Gretchen Krueger, and Ilya Sutskever. 2021. Learning Transferable Visual Models From Natural Language Supervision. In Proceedings of the 38th International Conference on Machine Learning, 2021, 18-24 July 2021, Virtual Event (Proceedings of Machine Learning Research, Vol. 139), Marina Meila and Tong Zhang (Eds.). PMLR, 8748-8763. http:\/\/proceedings.mlr.press\/v139\/radford21a.html"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240707"},{"key":"e_1_3_2_1_32_1","first-page":"65128","article-title":"Averitec: A dataset for real-world claim verification with evidence from the web","volume":"36","author":"Schlichtkrull Michael","year":"2023","unstructured":"Michael Schlichtkrull, Zhijiang Guo, and Andreas Vlachos. 2023. Averitec: A dataset for real-world claim verification with evidence from the web. Advances in Neural Information Processing Systems, Vol. 36 (2023), 65128-65167.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_33_1","first-page":"8612","article-title":"Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning","volume":"37","author":"Shao Hao","year":"2024","unstructured":"Hao Shao, Shengju Qian, Han Xiao, Guanglu Song, Zhuofan Zong, Letian Wang, Yu Liu, and Hongsheng Li. 2024. Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning. Advances in Neural Information Processing Systems, Vol. 37 (2024), 8612-8642.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_34_1","unstructured":"S Suryavardan Shreyash Mishra Parth Patwa Megha Chakraborty Anku Rani Aishwarya Reganti Aman Chadha Amitava Das Amit Sheth Manoj Chinnakotla et al. 2023. Factify 2: A multimodal fake news and satire news dataset. arXiv preprint arXiv:2304.03897 (2023)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3679826"},{"key":"e_1_3_2_1_36_1","unstructured":"Gemini Team Rohan Anil Sebastian Borgeaud Jean-Baptiste Alayrac Jiahui Yu Radu Soricut Johan Schalkwyk Andrew M Dai Anja Hauth Katie Millican et al. 2023. Gemini: a family of highly capable multimodal models. arXiv preprint arXiv:2312.11805 (2023)."},{"key":"e_1_3_2_1_37_1","volume-title":"Ryan Burnell, Libin Bai, Anmol Gulati, Garrett Tanzer, Damien Vincent, Zhufeng Pan, Shibo Wang, et al.","author":"Team Gemini","year":"2024","unstructured":"Gemini Team, Petko Georgiev, Ving Ian Lei, Ryan Burnell, Libin Bai, Anmol Gulati, Garrett Tanzer, Damien Vincent, Zhufeng Pan, Shibo Wang, et al., 2024. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context. arXiv preprint arXiv:2403.05530 (2024)."},{"key":"e_1_3_2_1_38_1","volume-title":"COVE: COntext and VEracity prediction for out-of-context images. arXiv preprint arXiv:2502.01194","author":"Tonglet Jonathan","year":"2025","unstructured":"Jonathan Tonglet, Gabriel Thiem, and Iryna Gurevych. 2025. COVE: COntext and VEracity prediction for out-of-context images. arXiv preprint arXiv:2502.01194 (2025)."},{"key":"e_1_3_2_1_39_1","volume-title":"MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models. arXiv preprint arXiv:2406.11288","author":"Wang Shengkang","year":"2024","unstructured":"Shengkang Wang, Hongzhan Lin, Ziyang Luo, Zhen Ye, Guang Chen, and Jing Ma. 2024. MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models. arXiv preprint arXiv:2406.11288 (2024)."},{"key":"e_1_3_2_1_40_1","volume-title":"Unified multimodal chain-of-thought reward model through reinforcement fine-tuning. arXiv preprint arXiv:2505.03318","author":"Wang Yibin","year":"2025","unstructured":"Yibin Wang, Zhimin Li, Yuhang Zang, Chunyu Wang, Qinglin Lu, Cheng Jin, and Jiaqi Wang. 2025. Unified multimodal chain-of-thought reward model through reinforcement fine-tuning. arXiv preprint arXiv:2505.03318 (2025)."},{"key":"e_1_3_2_1_41_1","unstructured":"xAI. 2025. Grok-4. https:\/\/x.ai\/grok. Large Language Model developed by xAI."},{"key":"e_1_3_2_1_42_1","volume-title":"Llava-o1: Let vision language models reason step-by-step. arXiv preprint arXiv:2411.10440","author":"Xu Guowei","year":"2024","unstructured":"Guowei Xu, Peng Jin, Li Hao, Yibing Song, Lichao Sun, and Li Yuan. 2024b. Llava-o1: Let vision language models reason step-by-step. arXiv preprint arXiv:2411.10440 (2024)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01284"},{"key":"e_1_3_2_1_44_1","volume-title":"LEMMA: towards lvlm-enhanced multimodal misinformation detection with external knowledge augmentation. arXiv preprint arXiv:2402.11943","author":"Xuan Keyang","year":"2024","unstructured":"Keyang Xuan, Li Yi, Fan Yang, Ruochen Wu, Yi R Fung, and Heng Ji. 2024. LEMMA: towards lvlm-enhanced multimodal misinformation detection with external knowledge augmentation. arXiv preprint arXiv:2402.11943 (2024)."},{"key":"e_1_3_2_1_45_1","volume-title":"End-to-end multimodal fact-checking and explanation generation: A challenging dataset and models. arXiv preprint arXiv:2205.12487","author":"Yao Barry Menglong","year":"2022","unstructured":"Barry Menglong Yao, Aditya Shah, Lichao Sun, Jin-Hee Cho, and Lifu Huang. 2022. End-to-end multimodal fact-checking and explanation generation: A challenging dataset and models. arXiv preprint arXiv:2205.12487 (2022)."},{"key":"e_1_3_2_1_46_1","volume-title":"Yi: Open foundation models by 01. ai. arXiv preprint arXiv:2403.04652","author":"Young Alex","year":"2024","unstructured":"Alex Young, Bei Chen, Chao Li, Chengen Huang, Ge Zhang, Guanwei Zhang, Guoyin Wang, Heng Li, Jiangcheng Zhu, Jianqun Chen, et al., 2024. Yi: Open foundation models by 01. ai. arXiv preprint arXiv:2403.04652 (2024)."},{"key":"e_1_3_2_1_47_1","volume-title":"Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning. arXiv preprint arXiv:2505.16836","author":"Zhang Fanrui","year":"2025","unstructured":"Fanrui Zhang, Dian Li, Qiang Zhang, Jun Chen, Gang Liu, Junxiong Lin, Jiahong Yan, Jiawei Liu, and Zheng-Jun Zha. 2025a. Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning. arXiv preprint arXiv:2505.16836 (2025)."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645455"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612183"},{"key":"e_1_3_2_1_50_1","unstructured":"Fanrui Zhang Qiang Zhang Sizhuo Zhou Jianwen Sun Chuanhao Li Jiaxin Ai Yukang Feng Yujie Zhang Wenjie Li Zizhen Li et al. 2025b. Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection. arXiv preprint arXiv:2512.16300 (2025)."},{"key":"e_1_3_2_1_51_1","volume-title":"MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models. arXiv preprint arXiv:2304.10592","author":"Zhu Deyao","year":"2023","unstructured":"Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny. 2023. MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models. arXiv preprint arXiv:2304.10592 (2023)."}],"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":[],"deposited":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:33:43Z","timestamp":1775838823000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774904.3792706"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":51,"alternative-id":["10.1145\/3774904.3792706","10.1145\/3774904"],"URL":"https:\/\/doi.org\/10.1145\/3774904.3792706","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"}}]}}