{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T05:23:22Z","timestamp":1769318602332,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62272261"],"award-info":[{"award-number":["62272261"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,3]]},"DOI":"10.1145\/3680207.3723494","type":"proceedings-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T13:19:18Z","timestamp":1763731158000},"page":"589-603","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["LLM-Explorer: Towards Efficient and Affordable LLM-based Exploration for Mobile Apps"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-4205-0770","authenticated-orcid":false,"given":"Shanhui","family":"Zhao","sequence":"first","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8450-7795","authenticated-orcid":false,"given":"Hao","family":"Wen","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4359-9217","authenticated-orcid":false,"given":"Wenjie","family":"Du","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0508-7199","authenticated-orcid":false,"given":"Cheng","family":"Liang","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications Beijing, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7352-8955","authenticated-orcid":false,"given":"Yunxin","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4925-5907","authenticated-orcid":false,"given":"Xiaozhou","family":"Ye","sequence":"additional","affiliation":[{"name":"AsiaInfo Technologies (China), Inc, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6195-6415","authenticated-orcid":false,"given":"Ye","family":"Ouyang","sequence":"additional","affiliation":[{"name":"AsiaInfo Technologies (China), Inc, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1591-2526","authenticated-orcid":false,"given":"Yuanchun","family":"Li","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University, Beijing, China"},{"name":"Shanghai Artificial Intelligence Laboratory, Shanghai, China"},{"name":"Beijing Academy of Artificial Intelligence (BAAI), Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3241539.3267768"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3197231.3197243"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1378600.1378626"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3371924"},{"key":"e_1_3_2_1_5_1","volume-title":"Xing","author":"Chiang Wei-Lin","year":"2023","unstructured":"Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023. Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality. https:\/\/lmsys.org\/blog\/2023-03-30-vicuna\/"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3126594.3126651"},{"key":"e_1_3_2_1_7_1","unstructured":"Android Developers. [n. d.]. UI\/Application Exerciser Monkey. https:\/\/developer.android.com\/studio\/test\/other-testing-tools\/monkey."},{"key":"e_1_3_2_1_8_1","volume-title":"On the creativity of large language models. arXiv preprint arXiv:2304.00008","author":"Franceschelli Giorgio","year":"2023","unstructured":"Giorgio Franceschelli and Mirco Musolesi. 2023. On the creativity of large language models. arXiv preprint arXiv:2304.00008 (2023)."},{"key":"e_1_3_2_1_9_1","volume-title":"AUITestAgent: Automatic Requirements Oriented GUI Function Testing. arXiv preprint arXiv:2407.09018","author":"Hu Yongxiang","year":"2024","unstructured":"Yongxiang Hu, Xuan Wang, Yingchuan Wang, Yu Zhang, Shiyu Guo, Chaoyi Chen, Xin Wang, and Yangfan Zhou. 2024. AUITestAgent: Automatic Requirements Oriented GUI Function Testing. arXiv preprint arXiv:2407.09018 (2024)."},{"key":"e_1_3_2_1_10_1","volume-title":"Automatic Macro Mining from Interaction Traces at Scale. arXiv preprint arXiv:2310.07023","author":"Huang Forrest","year":"2023","unstructured":"Forrest Huang, Gang Li, Tao Li, and Yang Li. 2023. Automatic Macro Mining from Interaction Traces at Scale. arXiv preprint arXiv:2310.07023 (2023)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287051"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3597503.3623344"},{"key":"e_1_3_2_1_13_1","volume-title":"select, derive, and recall: Augmenting llm with human-like memory for mobile task automation. arXiv preprint arXiv:2312.03003","author":"Lee Sunjae","year":"2023","unstructured":"Sunjae Lee, Junyoung Choi, Jungjae Lee, Hojun Choi, Steven Y Ko, Sangeun Oh, and Insik Shin. 2023. Explore, select, derive, and recall: Augmenting llm with human-like memory for mobile task automation. arXiv preprint arXiv:2312.03003 (2023)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2020.3021987"},{"key":"e_1_3_2_1_15_1","unstructured":"Yuanchun Li Hao Wen Weijun Wang et al. 2024. Personal LLM Agents: Insights and Survey about the Capability Efficiency and Security. arXiv preprint arXiv:2401.05459 (2024)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-C.2017.8"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE.2019.00104"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2639108.2639131"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3570361.3613259"},{"key":"e_1_3_2_1_20_1","volume-title":"AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. arXiv","author":"Lin Ji","year":"2023","unstructured":"Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Xingyu Dang, and Song Han. 2023. AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. arXiv (2023)."},{"key":"e_1_3_2_1_21_1","volume-title":"Proceedings of the 45th International Conference on Software Engineering (ICSE). IEEE\/ACM.","author":"Liu Zhe","year":"2023","unstructured":"Zhe Liu, Chunyang Chen, Junjie Wang, et al. 2023. Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions. In Proceedings of the 45th International Conference on Software Engineering (ICSE). IEEE\/ACM."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00119"},{"key":"e_1_3_2_1_23_1","volume-title":"Vision-driven Automated Mobile GUI Testing via Multimodal Large Language Model. arXiv preprint arXiv:2407.03037","author":"Liu Zhe","year":"2024","unstructured":"Zhe Liu, Cheng Li, Chunyang Chen, Junjie Wang, Boyu Wu, Yawen Wang, Jun Hu, and Qing Wang. 2024. Vision-driven Automated Mobile GUI Testing via Multimodal Large Language Model. arXiv preprint arXiv:2407.03037 (2024)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2491411.2491450"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2931037.2931054"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3395363.3397354"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3502868"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2018.2141024"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3580895"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2024.3368208"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3238147.3240465"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3671016.3671404"},{"key":"e_1_3_2_1_33_1","volume-title":"Denny Zhou, et al.","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 35 (2022), 24824\u201324837."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3636534.3649379"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.3390\/sym13020310"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE51524.2021.9678778"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE51524.2021.9678778"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/2462456.2465717"},{"key":"e_1_3_2_1_39_1","volume-title":"Autonomous Large Language Model Agents Enabling Intent-Driven Mobile GUI Testing. arXiv preprint arXiv:2311.08649 (ICST 2024)","author":"Yoon Juyeon","year":"2023","unstructured":"Juyeon Yoon, Robert Feldt, and Shin Yoo. 2023. Autonomous Large Language Model Agents Enabling Intent-Driven Mobile GUI Testing. arXiv preprint arXiv:2311.08649 (ICST 2024) (2023)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3032970.3032972"}],"event":{"name":"ACM MOBICOM '25: 31st Annual International Conference on Mobile Computing and Networking","location":"Kerry Hotel, Hong Kong Hong Kong China","acronym":"ACM MOBICOM '25","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"]},"container-title":["Proceedings of the 31st Annual International Conference on Mobile Computing and Networking"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3680207.3723494","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T13:19:41Z","timestamp":1763731181000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3680207.3723494"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,3]]},"references-count":40,"alternative-id":["10.1145\/3680207.3723494","10.1145\/3680207"],"URL":"https:\/\/doi.org\/10.1145\/3680207.3723494","relation":{},"subject":[],"published":{"date-parts":[[2025,11,3]]},"assertion":[{"value":"2025-11-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}