{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T19:45:30Z","timestamp":1765309530924,"version":"3.46.0"},"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":["62306342, 62236004, 62206078, 62476073"],"award-info":[{"award-number":["62306342, 62236004, 62206078, 62476073"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific Research Fund of Hunan Provincial Education Department","award":["24B0001"],"award-info":[{"award-number":["24B0001"]}]},{"name":"Excellent Young Scientists Fund in Hunan Province","award":["2024JJ4070"],"award-info":[{"award-number":["2024JJ4070"]}]},{"name":"Science and Technology Innovation Program of Hunan Province","award":["2024RC3024"],"award-info":[{"award-number":["2024RC3024"]}]},{"name":"CCF-Zhipu Large Model Innovation Fund","award":["CCF-Zhipu202406"],"award-info":[{"award-number":["CCF-Zhipu202406"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"DOI":"10.1145\/3746027.3755790","type":"proceedings-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T06:54:17Z","timestamp":1761375257000},"page":"5188-5197","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["MPCC: A Novel Benchmark for Multimodal Planning with Complex Constraints in Multimodal Large Language Models"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-9363-5315","authenticated-orcid":false,"given":"Yiyan","family":"Ji","sequence":"first","affiliation":[{"name":"Harbin Institute of Technology, Harbin, Heilongjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7511-0286","authenticated-orcid":false,"given":"Haoran","family":"Chen","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology, Harbin, Heilongjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9154-7858","authenticated-orcid":false,"given":"Qiguang","family":"Chen","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology, Harbin, Heilongjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5207-4173","authenticated-orcid":false,"given":"Chengyue","family":"Wu","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3619-675X","authenticated-orcid":false,"given":"Libo","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, Hunan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3907-0335","authenticated-orcid":false,"given":"Wanxiang","family":"Che","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology, Harbin, Heilongjiang, China"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al.","author":"Achiam Josh","year":"2023","unstructured":"Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al., 2023. Gpt-4 technical report. arXiv preprint arXiv:2303.08774."},{"key":"e_1_3_2_1_2_1","volume-title":"Towards reasoning era: A survey of long chain-of-thought for reasoning large language models. arXiv preprint arXiv:2503.09567","author":"Chen Qiguang","year":"2025","unstructured":"Qiguang Chen, Libo Qin, Jinhao Liu, Dengyun Peng, Jiannan Guan, Peng Wang, Mengkang Hu, Yuhang Zhou, Te Gao, and Wangxiang Che. 2025a. Towards reasoning era: A survey of long chain-of-thought for reasoning large language models. arXiv preprint arXiv:2503.09567 (2025)."},{"key":"e_1_3_2_1_3_1","volume-title":"ECM: A Unified Electronic Circuit Model for Explaining the Emergence of In-Context Learning and Chain-of-Thought in Large Language Model. arXiv preprint arXiv:2502.03325","author":"Chen Qiguang","year":"2025","unstructured":"Qiguang Chen, Libo Qin, Jinhao Liu, Dengyun Peng, Jiaqi Wang, Mengkang Hu, Zhi Chen, Wanxiang Che, and Ting Liu. 2025b. ECM: A Unified Electronic Circuit Model for Explaining the Emergence of In-Context Learning and Chain-of-Thought in Large Language Model. arXiv preprint arXiv:2502.03325 (2025)."},{"key":"e_1_3_2_1_4_1","volume-title":"Proc. of NeurIPS.","author":"Chen Qiguang","year":"2024","unstructured":"Qiguang Chen, Libo Qin, Jiaqi Wang, Jingxuan Zhou, and Wanxiang Che. 2024a. Unlocking the capabilities of thought: A reasoning boundary framework to quantify and optimize chain-of-thought. In Proc. of NeurIPS."},{"key":"e_1_3_2_1_5_1","volume-title":"Proc. of ACL.","author":"Chen Qiguang","year":"2024","unstructured":"Qiguang Chen, Libo Qin, Jin Zhang, Zhi Chen, Xiao Xu, and Wanxiang Che. 2024b. M ^3 CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought. In Proc. of ACL."},{"key":"e_1_3_2_1_6_1","volume-title":"Egoplan-bench: Benchmarking egocentric embodied planning with multimodal large language models. CoRR","author":"Chen Yi","year":"2023","unstructured":"Yi Chen, Yuying Ge, Yixiao Ge, Mingyu Ding, Bohao Li, Rui Wang, Ruifeng Xu, Ying Shan, and Xihui Liu. 2023. Egoplan-bench: Benchmarking egocentric embodied planning with multimodal large language models. CoRR (2023)."},{"key":"e_1_3_2_1_7_1","first-page":"24185","article-title":"Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks","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., 2024c. Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks. In Proc. of CVPR. 24185-24198.","journal-title":"Proc. of CVPR."},{"key":"e_1_3_2_1_8_1","volume-title":"Zhi Chen, Wanxiang Che, et al.","author":"Cheng Zihui","year":"2025","unstructured":"Zihui Cheng, Qiguang Chen, Xiao Xu, Jiaqi Wang, Weiyun Wang, Hao Fei, Yidong Wang, Alex Jinpeng Wang, Zhi Chen, Wanxiang Che, et al., 2025a. Visual Thoughts: A Unified Perspective of Understanding Multimodal Chain-of-Thought. arXiv preprint arXiv:2505.15510 (2025)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i22.34538"},{"key":"e_1_3_2_1_10_1","unstructured":"Qingxiu Dong Lei Li Damai Dai Ce Zheng Jingyuan Ma Rui Li Heming Xia Jingjing Xu Zhiyong Wu Tianyu Liu et al. 2022. A survey on in-context learning. arXiv preprint arXiv:2301.00234 (2022)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3685520"},{"key":"e_1_3_2_1_12_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_13_1","volume-title":"Proc. of NeurIPS.","author":"Kil Jihyung","year":"2024","unstructured":"Jihyung Kil, Zheda Mai, Justin Lee, Arpita Chowdhury, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, and Wei-Lun Harry Chao. 2024. Mllm-compbench: A comparative reasoning benchmark for multimodal llms. In Proc. of NeurIPS."},{"key":"e_1_3_2_1_14_1","volume-title":"Po-Yu Huang","author":"Koh Jing Yu","year":"2024","unstructured":"Jing Yu Koh, Robert Lo, Lawrence Jang, Vikram Duvvur, Ming Chong Lim, Po-Yu Huang, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, and Daniel Fried. 2024a. Visualwebarena: Evaluating multimodal agents on realistic visual web tasks. arXiv preprint arXiv:2401.13649 (2024)."},{"key":"e_1_3_2_1_15_1","unstructured":"Jing Yu Koh Stephen McAleer Daniel Fried and Ruslan Salakhutdinov. 2024b. Tree Search for Language Model Agents. arXiv:2407.01476 [cs.AI] https:\/\/arxiv.org\/abs\/2407.01476"},{"key":"e_1_3_2_1_16_1","volume-title":"Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa.","author":"Kojima Takeshi","year":"2022","unstructured":"Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022. Large language models are zero-shot reasoners."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01263"},{"key":"e_1_3_2_1_18_1","unstructured":"Bo Li Yuanhan Zhang Dong Guo Renrui Zhang Feng Li Hao Zhang Kaichen Zhang Peiyuan Zhang Yanwei Li Ziwei Liu and Chunyuan Li. 2024c. LLaVA-OneVision: Easy Visual Task Transfer. arXiv:2408.03326 [cs.CV] https:\/\/arxiv.org\/abs\/2408.03326"},{"key":"e_1_3_2_1_19_1","volume-title":"Conference on Robot Learning. PMLR, 80-93","author":"Li Chengshu","year":"2023","unstructured":"Chengshu Li, Ruohan Zhang, Josiah Wong, Cem Gokmen, Sanjana Srivastava, Roberto Mart\u00edn-Mart\u00edn, Chen Wang, Gabrael Levine, Michael Lingelbach, Jiankai Sun, et al., 2023. Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation. In Conference on Robot Learning. PMLR, 80-93."},{"key":"e_1_3_2_1_20_1","volume-title":"Jeff Nichols, Yinfei Yang, and Zhe Gan.","author":"Li Zhangheng","year":"2024","unstructured":"Zhangheng Li, Keen You, Haotian Zhang, Di Feng, Harsh Agrawal, Xiujun Li, Mohana Prasad Sathya Moorthy, Jeff Nichols, Yinfei Yang, and Zhe Gan. 2024b. Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms. arXiv:2410.18967 [cs.CV] https:\/\/arxiv.org\/abs\/2410.18967"},{"key":"e_1_3_2_1_21_1","volume-title":"Michael Yu Wang, and Liqiang Nie","author":"Lv Qi","year":"2024","unstructured":"Qi Lv, Hao Li, Xiang Deng, Rui Shao, Michael Yu Wang, and Liqiang Nie. 2024. RoboMP ^2: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models. arXiv preprint arXiv:2404.04929 (2024)."},{"key":"e_1_3_2_1_22_1","volume-title":"Janusflow: Harmonizing autoregression and rectified flow for unified multimodal understanding and generation. arXiv preprint arXiv:2411.07975","author":"Ma Yiyang","year":"2024","unstructured":"Yiyang Ma, Xingchao Liu, Xiaokang Chen, Wen Liu, Chengyue Wu, Zhiyu Wu, Zizheng Pan, Zhenda Xie, Haowei Zhang, Liang Zhao, et al., 2024b. Janusflow: Harmonizing autoregression and rectified flow for unified multimodal understanding and generation. arXiv preprint arXiv:2411.07975 (2024)."},{"volume-title":"Proc","author":"Ma Zixian","key":"e_1_3_2_1_23_1","unstructured":"Zixian Ma, Weikai Huang, Jieyu Zhang, Tanmay Gupta, and Ranjay Krishna. 2024a. m & m's: A Benchmark to Evaluate Tool-Use for m ulti-step m ulti-modal Tasks. In Proc. of ECCV. Springer, 18-34."},{"key":"e_1_3_2_1_24_1","first-page":"42748","article-title":"Perception test: A diagnostic benchmark for multimodal video models","volume":"36","author":"Patraucean Viorica","year":"2023","unstructured":"Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adria Recasens, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Mateusz Malinowski, Yi Yang, Carl Doersch, et al., 2023. Perception test: A diagnostic benchmark for multimodal video models. In Proc. of NeurIPS, Vol. 36. 42748-42761.","journal-title":"Proc. of NeurIPS"},{"key":"e_1_3_2_1_25_1","volume-title":"What factors affect multi-modal in-context learning? an in-depth exploration. arXiv preprint arXiv:2410.20482","author":"Qin Libo","year":"2024","unstructured":"Libo Qin, Qiguang Chen, Hao Fei, Zhi Chen, Min Li, and Wanxiang Che. 2024. What factors affect multi-modal in-context learning? an in-depth exploration. arXiv preprint arXiv:2410.20482 (2024)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1950365.1950386"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01075"},{"key":"e_1_3_2_1_28_1","unstructured":"Gemini Team Rohan Anil Sebastian Borgeaud Yonghui Wu Jean-Baptiste Alayrac Jiahui Yu Radu Soricut Johan Schalkwyk Andrew M Dai Anja Hauth et al. 2023. Gemini: a family of highly capable multimodal models. arXiv preprint arXiv:2312.11805 (2023)."},{"key":"e_1_3_2_1_29_1","volume-title":"QVQ: To See the World with Wisdom.","author":"Team Qwen","year":"2024","unstructured":"Qwen Team. 2024. QVQ: To See the World with Wisdom."},{"key":"e_1_3_2_1_30_1","unstructured":"Karthik Valmeekam Matthew Marquez Alberto Olmo Sarath Sreedharan and Subbarao Kambhampati. 2023. PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change. arXiv:2206.10498 [cs.CL] https:\/\/arxiv.org\/abs\/2206.10498"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Fengxiang Wang Hongzhen Wang Mingshuo Chen Di Wang Yulin Wang Zonghao Guo Qiang Ma Long Lan Wenjing Yang Jing Zhang Zhiyuan Liu and Maosong Sun. 2025. XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra-High-Resolution Remote Sensing Imagery? arXiv:2503.23771 [cs.CV] https:\/\/arxiv.org\/abs\/2503.23771","DOI":"10.1109\/CVPR52734.2025.01336"},{"key":"e_1_3_2_1_32_1","volume-title":"Roy Ka-Wei Lee, and Ee-Peng Lim","author":"Wang Lei","year":"2023","unstructured":"Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, and Ee-Peng Lim. 2023. Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models. arXiv preprint arXiv:2305.04091 (2023)."},{"key":"e_1_3_2_1_33_1","volume-title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution. arXiv preprint arXiv:2409.12191","author":"Wang Peng","year":"2024","unstructured":"Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Yang Fan, Kai Dang, Mengfei Du, Xuancheng Ren, Rui Men, Dayiheng Liu, Chang Zhou, Jingren Zhou, and Junyang Lin. 2024a. Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution. arXiv preprint arXiv:2409.12191 (2024)."},{"key":"e_1_3_2_1_34_1","volume-title":"S3 agent: Unlocking the power of VLLM for zero-shot multi-modal sarcasm detection. ACM Transactions on Multimedia Computing, Communications and Applications","author":"Wang Peng","year":"2024","unstructured":"Peng Wang, Yongheng Zhang, Hao Fei, Qiguang Chen, Yukai Wang, Jiasheng Si, Wenpeng Lu, Min Li, and Libo Qin. 2024b. S3 agent: Unlocking the power of VLLM for zero-shot multi-modal sarcasm detection. ACM Transactions on Multimedia Computing, Communications and Applications (2024)."},{"key":"e_1_3_2_1_35_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. In Proc. of NeurIPS, Vol. 35. 24824-24837.","journal-title":"Proc. of NeurIPS"},{"key":"e_1_3_2_1_36_1","volume-title":"Janus: Decoupling visual encoding for unified multimodal understanding and generation. arXiv preprint arXiv:2410.13848","author":"Wu Chengyue","year":"2024","unstructured":"Chengyue Wu, Xiaokang Chen, Zhiyu Wu, Yiyang Ma, Xingchao Liu, Zizheng Pan, Wen Liu, Zhenda Xie, Xingkai Yu, Chong Ruan, et al., 2024b. Janus: Decoupling visual encoding for unified multimodal understanding and generation. arXiv preprint arXiv:2410.13848 (2024)."},{"key":"e_1_3_2_1_37_1","unstructured":"Zhiyu Wu Xiaokang Chen Zizheng Pan Xingchao Liu Wen Liu Damai Dai Huazuo Gao Yiyang Ma Chengyue Wu Bingxuan Wang et al. 2024a. Deepseek-vl2: Mixture-of-experts vision-language models for advanced multimodal understanding. arXiv preprint arXiv:2412.10302 (2024)."},{"key":"e_1_3_2_1_38_1","volume-title":"Logicvista: Multimodal llm logical reasoning benchmark in visual contexts. arXiv preprint arXiv:2407.04973","author":"Xiao Yijia","year":"2024","unstructured":"Yijia Xiao, Edward Sun, Tianyu Liu, and Wei Wang. 2024. Logicvista: Multimodal llm logical reasoning benchmark in visual contexts. arXiv preprint arXiv:2407.04973 (2024)."},{"key":"e_1_3_2_1_39_1","first-page":"52040","article-title":"Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments","volume":"37","author":"Xie Tianbao","year":"2024","unstructured":"Tianbao Xie, Danyang Zhang, Jixuan Chen, Xiaochuan Li, Siheng Zhao, Ruisheng Cao, Jing Hua Toh, Zhoujun Cheng, Dongchan Shin, Fangyu Lei, et al., 2024. Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments. In Proc. of NeurIPS, Vol. 37. 52040-52094.","journal-title":"Proc. of NeurIPS"},{"key":"e_1_3_2_1_40_1","unstructured":"Zhengyuan Yang Linjie Li Jianfeng Wang Kevin Lin Ehsan Azarnasab Faisal Ahmed Zicheng Liu Ce Liu Michael Zeng and Lijuan Wang. 2023. MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action. arXiv:2303.11381 [cs.CV] https:\/\/arxiv.org\/abs\/2303.11381"},{"key":"e_1_3_2_1_41_1","volume-title":"Mmt-bench: A comprehensive multimodal benchmark for evaluating large vision-language models towards multitask agi. arXiv preprint arXiv:2404.16006","author":"Ying Kaining","year":"2024","unstructured":"Kaining Ying, Fanqing Meng, Jin Wang, Zhiqian Li, Han Lin, Yue Yang, Hao Zhang, Wenbo Zhang, Yuqi Lin, Shuo Liu, et al., 2024. Mmt-bench: A comprehensive multimodal benchmark for evaluating large vision-language models towards multitask agi. arXiv preprint arXiv:2404.16006 (2024)."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00913"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"Weichen Zhan Zile Zhou Zhiheng Zheng Chen Gao Jinqiang Cui Yong Li Xinlei Chen and Xiao-Ping Zhang. 2025. Open3DVQA: A Benchmark for Comprehensive Spatial Reasoning with Multimodal Large Language Model in Open Space. arXiv:2503.11094 [cs.CV] https:\/\/arxiv.org\/abs\/2503.11094","DOI":"10.1145\/3746027.3758219"},{"key":"e_1_3_2_1_44_1","volume-title":"Chi, and Denny Zhou","author":"Zheng Huaixiu Steven","year":"2024","unstructured":"Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, and Denny Zhou. 2024. NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. arXiv:2406.04520 [cs.CL] https:\/\/arxiv.org\/abs\/2406.04520"},{"key":"e_1_3_2_1_45_1","volume-title":"Webarena: A realistic web environment for building autonomous agents. arXiv preprint arXiv:2307.13854","author":"Zhou Shuyan","year":"2023","unstructured":"Shuyan Zhou, Frank F Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, et al., 2023. Webarena: A realistic web environment for building autonomous agents. arXiv preprint arXiv:2307.13854 (2023)."}],"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\/3746027.3755790","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T19:41:01Z","timestamp":1765309261000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746027.3755790"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":45,"alternative-id":["10.1145\/3746027.3755790","10.1145\/3746027"],"URL":"https:\/\/doi.org\/10.1145\/3746027.3755790","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"}}]}}