{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T03:51:08Z","timestamp":1772596268842,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Tsinghua University (Department of Computer Science and Technology) -Siemens Ltd., China Joint Research Center for Industrial Intelligence and Internet of Things (JCIIOT)"},{"name":"NSFC","award":["62276148,62425601"],"award-info":[{"award-number":["62276148,62425601"]}]},{"name":"New Cornerstone Science Foundation - XPLORER PRIZE"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671620","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"5295-5306","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":29,"title":["AutoWebGLM: A Large Language Model-based Web Navigating Agent"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3106-320X","authenticated-orcid":false,"given":"Hanyu","family":"Lai","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9226-4569","authenticated-orcid":false,"given":"Xiao","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University &amp; Zhipu AI, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3580-7851","authenticated-orcid":false,"given":"Iat Long","family":"Iong","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2650-3910","authenticated-orcid":false,"given":"Shuntian","family":"Yao","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8270-1289","authenticated-orcid":false,"given":"Yuxuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8203-9967","authenticated-orcid":false,"given":"Pengbo","family":"Shen","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1695-8499","authenticated-orcid":false,"given":"Hao","family":"Yu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-3292-8757","authenticated-orcid":false,"given":"Hanchen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3295-7758","authenticated-orcid":false,"given":"Xiaohan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Zhipu AI, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6092-2002","authenticated-orcid":false,"given":"Yuxiao","family":"Dong","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3487-4593","authenticated-orcid":false,"given":"Jie","family":"Tang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_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 (2023)."},{"key":"e_1_3_2_2_2_1","unstructured":"Anthropic. 2023. Model Card and Evaluations for Claude Models. (2023)."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553380"},{"key":"e_1_3_2_2_4_1","volume-title":"Proceedings of the 2013 conference on empirical methods in natural language processing. 1533--1544","author":"Berant Jonathan","year":"2013","unstructured":"Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013. Semantic parsing on freebase from question-answer pairs. In Proceedings of the 2013 conference on empirical methods in natural language processing. 1533--1544."},{"key":"e_1_3_2_2_5_1","volume-title":"Black-box prompt optimization: Aligning large language models without model training. arXiv preprint arXiv:2311.04155","author":"Cheng Jiale","year":"2023","unstructured":"Jiale Cheng, Xiao Liu, Kehan Zheng, Pei Ke, Hongning Wang, Yuxiao Dong, Jie Tang, and Minlie Huang. 2023. Black-box prompt optimization: Aligning large language models without model training. arXiv preprint arXiv:2311.04155 (2023)."},{"key":"e_1_3_2_2_6_1","volume-title":"SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents. arXiv preprint arXiv:2401.10935","author":"Cheng Kanzhi","year":"2024","unstructured":"Kanzhi Cheng, Qiushi Sun, Yougang Chu, Fangzhi Xu, Yantao Li, Jianbing Zhang, and Zhiyong Wu. 2024. SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents. arXiv preprint arXiv:2401.10935 (2024)."},{"key":"e_1_3_2_2_7_1","volume-title":"Mind2Web: Towards a Generalist Agent for the Web. arXiv preprint arXiv:2306.06070","author":"Deng Xiang","year":"2023","unstructured":"Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samuel Stevens, Boshi Wang, Huan Sun, and Yu Su. 2023. Mind2Web: Towards a Generalist Agent for the Web. arXiv preprint arXiv:2306.06070 (2023)."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.26"},{"key":"e_1_3_2_2_9_1","volume-title":"Mustafa Safdari, Yutaka Matsuo, Douglas Eck, and Aleksandra Faust.","author":"Gur Izzeddin","year":"2023","unstructured":"Izzeddin Gur, Hiroki Furuta, Austin Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, and Aleksandra Faust. 2023. A real-world webagent with planning, long context understanding, and program synthesis. arXiv preprint arXiv:2307.12856 (2023)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"crossref","unstructured":"Wenyi Hong Weihan Wang Qingsong Lv Jiazheng Xu Wenmeng Yu Junhui Ji Yan Wang Zihan Wang Yuxiao Dong Ming Ding et al. 2023. CogAgent: A Visual Language Model for GUI Agents. arXiv preprint arXiv:2312.08914 (2023).","DOI":"10.1109\/CVPR52733.2024.01354"},{"key":"e_1_3_2_2_11_1","volume-title":"Unnatural instructions: Tuning language models with (almost) no human labor. arXiv preprint arXiv:2212.09689","author":"Honovich Or","year":"2022","unstructured":"Or Honovich, Thomas Scialom, Omer Levy, and Timo Schick. 2022. Unnatural instructions: Tuning language models with (almost) no human labor. arXiv preprint arXiv:2212.09689 (2022)."},{"key":"e_1_3_2_2_12_1","volume-title":"International Conference on Machine Learning. PMLR, 9466--9482","author":"Humphreys Peter C","year":"2022","unstructured":"Peter C Humphreys, David Raposo, Tobias Pohlen, Gregory Thornton, Rachita Chhaparia, Alistair Muldal, Josh Abramson, Petko Georgiev, Adam Santoro, and Timothy Lillicrap. 2022. A data-driven approach for learning to control computers. In International Conference on Machine Learning. PMLR, 9466--9482."},{"key":"e_1_3_2_2_13_1","volume-title":"Wayne Xin Zhao, and Ji-Rong Wen","author":"Jiang Jinhao","year":"2023","unstructured":"Jinhao Jiang, Kun Zhou, Zican Dong, Keming Ye, Wayne Xin Zhao, and Ji-Rong Wen. 2023. Structgpt: A general framework for large language model to reason over structured data. arXiv preprint arXiv:2305.09645 (2023)."},{"key":"e_1_3_2_2_14_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. Advances in neural information processing systems, Vol. 35 (2022), 22199--22213."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00276"},{"key":"e_1_3_2_2_16_1","volume-title":"WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences. arXiv preprint arXiv:2306.07906","author":"Liu Xiao","year":"2023","unstructured":"Xiao Liu, Hanyu Lai, Hao Yu, Yifan Xu, Aohan Zeng, Zhengxiao Du, Peng Zhang, Yuxiao Dong, and Jie Tang. 2023. WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences. arXiv preprint arXiv:2306.07906 (2023)."},{"key":"e_1_3_2_2_17_1","volume-title":"WizardCoder: Empowering Code Large Language Models with Evol-Instruct. arXiv preprint arXiv:2306.08568","author":"Luo Ziyang","year":"2023","unstructured":"Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, and Daxin Jiang. 2023. WizardCoder: Empowering Code Large Language Models with Evol-Instruct. arXiv preprint arXiv:2306.08568 (2023)."},{"key":"e_1_3_2_2_18_1","first-page":"462","article-title":"Generating training data with language models: Towards zero-shot language understanding","volume":"35","author":"Meng Yu","year":"2022","unstructured":"Yu Meng, Jiaxin Huang, Yu Zhang, and Jiawei Han. 2022. Generating training data with language models: Towards zero-shot language understanding. Advances in Neural Information Processing Systems, Vol. 35 (2022), 462--477.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2019.8759448"},{"key":"e_1_3_2_2_20_1","volume-title":"Orca: Progressive learning from complex explanation traces of gpt-4. arXiv preprint arXiv:2306.02707","author":"Mukherjee Subhabrata","year":"2023","unstructured":"Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, Sahaj Agarwal, Hamid Palangi, and Ahmed Awadallah. 2023. Orca: Progressive learning from complex explanation traces of gpt-4. arXiv preprint arXiv:2306.02707 (2023)."},{"key":"e_1_3_2_2_21_1","volume-title":"Webgpt: Browser-assisted question-answering with human feedback. arXiv preprint arXiv:2112.09332","author":"Nakano Reiichiro","year":"2021","unstructured":"Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al. 2021. Webgpt: Browser-assisted question-answering with human feedback. arXiv preprint arXiv:2112.09332 (2021)."},{"key":"e_1_3_2_2_22_1","volume-title":"MS MARCO: A human generated machine reading comprehension dataset. choice","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. choice, Vol. 2640 (2016), 660."},{"key":"e_1_3_2_2_23_1","unstructured":"OpenAI. 2022. Introducing chatgpt. (2022)."},{"key":"e_1_3_2_2_24_1","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume":"35","author":"Ouyang Long","year":"2022","unstructured":"Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022. Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems, Vol. 35 (2022), 27730--27744.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_25_1","volume-title":"Instruction tuning with gpt-4. arXiv preprint arXiv:2304.03277","author":"Peng Baolin","year":"2023","unstructured":"Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, and Jianfeng Gao. 2023. Instruction tuning with gpt-4. arXiv preprint arXiv:2304.03277 (2023)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Ofir Press Muru Zhang Sewon Min Ludwig Schmidt Noah A Smith and Mike Lewis. 2022. Measuring and Narrowing the Compositionality Gap in Language Models. (2022).","DOI":"10.18653\/v1\/2023.findings-emnlp.378"},{"key":"e_1_3_2_2_27_1","volume-title":"Direct preference optimization: Your language model is secretly a reward model. arXiv preprint arXiv:2305.18290","author":"Rafailov Rafael","year":"2023","unstructured":"Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D Manning, and Chelsea Finn. 2023. Direct preference optimization: Your language model is secretly a reward model. arXiv preprint arXiv:2305.18290 (2023)."},{"key":"e_1_3_2_2_28_1","volume-title":"100,000 questions for machine comprehension of text. arXiv preprint arXiv:1606.05250","author":"Rajpurkar Pranav","year":"2016","unstructured":"Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016. Squad: 100,000 questions for machine comprehension of text. arXiv preprint arXiv:1606.05250 (2016)."},{"key":"e_1_3_2_2_29_1","volume-title":"Fran\u00e7ois Yvon, Matthias Gall\u00e9, et al.","author":"Scao Teven Le","year":"2022","unstructured":"Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ili\u0107, Daniel Hesslow, Roman Castagn\u00e9, Alexandra Sasha Luccioni, Fran\u00e7ois Yvon, Matthias Gall\u00e9, et al. 2022. Bloom: A 176b-parameter open-access multilingual language model. arXiv preprint arXiv:2211.05100 (2022)."},{"key":"e_1_3_2_2_30_1","volume-title":"Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971","author":"Touvron Hugo","year":"2023","unstructured":"Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth\u00e9e Lacroix, Baptiste Rozi\u00e8re, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023. Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023)."},{"key":"e_1_3_2_2_31_1","unstructured":"Hugo Touvron Louis Martin Kevin Stone Peter Albert Amjad Almahairi Yasmine Babaei Nikolay Bashlykov Soumya Batra Prajjwal Bhargava Shruti Bhosale et al. 2023. Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288 (2023)."},{"key":"e_1_3_2_2_32_1","volume-title":"Zhewei Wei, and Ji-Rong Wen.","author":"Wang Lei","year":"2023","unstructured":"Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, Wayne Xin Zhao, Zhewei Wei, and Ji-Rong Wen. 2023. A Survey on Large Language Model based Autonomous Agents. arXiv preprint arXiv:2308.11432 (2023)."},{"key":"e_1_3_2_2_33_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_2_34_1","first-page":"4555","article-title":"A survey on curriculum learning","volume":"44","author":"Wang Xin","year":"2021","unstructured":"Xin Wang, Yudong Chen, and Wenwu Zhu. 2021. A survey on curriculum learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 44, 9 (2021), 4555--4576.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_2_35_1","volume-title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models. In The Eleventh International Conference on Learning Representations.","author":"Wang Xuezhi","year":"2022","unstructured":"Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022. Self-Consistency Improves Chain of Thought Reasoning in Language Models. In The Eleventh International Conference on Learning Representations."},{"key":"e_1_3_2_2_36_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_2_37_1","volume-title":"The Rise and Potential of Large Language Model Based Agents: A Survey. arXiv preprint arXiv:2309.07864","author":"Xi Zhiheng","year":"2023","unstructured":"Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, Rui Zheng, Xiaoran Fan, Xiao Wang, Limao Xiong, Yuhao Zhou, Weiran Wang, Changhao Jiang, Yicheng Zou, Xiangyang Liu, Zhangyue Yin, Shihan Dou, Rongxiang Weng, Wensen Cheng, Qi Zhang, Wenjuan Qin, Yongyan Zheng, Xipeng Qiu, Xuanjing Huang, and Tao Gui. 2023. The Rise and Potential of Large Language Model Based Agents: A Survey. arXiv preprint arXiv:2309.07864 (2023)."},{"key":"e_1_3_2_2_38_1","volume-title":"Wizardlm: Empowering large language models to follow complex instructions. arXiv preprint arXiv:2304.12244","author":"Xu Can","year":"2023","unstructured":"Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, and Daxin Jiang. 2023. Wizardlm: Empowering large language models to follow complex instructions. arXiv preprint arXiv:2304.12244 (2023)."},{"key":"e_1_3_2_2_39_1","volume-title":"Lemur: Harmonizing natural language and code for language agents. arXiv preprint arXiv:2310.06830","author":"Xu Yiheng","year":"2023","unstructured":"Yiheng Xu, Hongjin Su, Chen Xing, Boyu Mi, Qian Liu, Weijia Shi, Binyuan Hui, Fan Zhou, Yitao Liu, Tianbao Xie, et al. 2023. Lemur: Harmonizing natural language and code for language agents. arXiv preprint arXiv:2310.06830 (2023)."},{"key":"e_1_3_2_2_40_1","volume-title":"ReAct: Synergizing Reasoning and Acting in Language Models. In The Eleventh International Conference on Learning Representations.","author":"Yao Shunyu","year":"2022","unstructured":"Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao. 2022. ReAct: Synergizing Reasoning and Acting in Language Models. In The Eleventh International Conference on Learning Representations."},{"key":"e_1_3_2_2_41_1","volume-title":"Scaling relationship on learning mathematical reasoning with large language models. arXiv preprint arXiv:2308.01825","author":"Yuan Zheng","year":"2023","unstructured":"Zheng Yuan, Hongyi Yuan, Chengpeng Li, Guanting Dong, Chuanqi Tan, and Chang Zhou. 2023. Scaling relationship on learning mathematical reasoning with large language models. arXiv preprint arXiv:2308.01825 (2023)."},{"key":"e_1_3_2_2_42_1","volume-title":"The Eleventh International Conference on Learning Representations.","author":"Zeng Aohan","year":"2022","unstructured":"Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, et al. 2022. GLM-130B: An Open Bilingual Pre-trained Model. In The Eleventh International Conference on Learning Representations."},{"key":"e_1_3_2_2_43_1","volume-title":"Xi Victoria Lin, et al","author":"Zhang Susan","year":"2022","unstructured":"Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022. Opt: Open pre-trained transformer language models. arXiv preprint arXiv:2205.01068 (2022)."},{"key":"e_1_3_2_2_44_1","unstructured":"Wayne Xin Zhao Kun Zhou Junyi Li Tianyi Tang Xiaolei Wang Yupeng Hou Yingqian Min Beichen Zhang Junjie Zhang Zican Dong et al. 2023. A survey of large language models. arXiv preprint arXiv:2303.18223 (2023)."},{"key":"e_1_3_2_2_45_1","volume-title":"WebArena: A Realistic Web Environment for Building Autonomous Agents. In Second Agent Learning in Open-Endedness Workshop.","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. In Second Agent Learning in Open-Endedness Workshop."}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Barcelona Spain","acronym":"KDD '24","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671620","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671620","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:05:59Z","timestamp":1750291559000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671620"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":45,"alternative-id":["10.1145\/3637528.3671620","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671620","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}