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This paper introduces DroidBot-GPT, a tool that utilizes GPT-like large language models (LLMs) to automate the interactions with Android mobile applications.
Dynodroid: An input generation system for android apps
Aravind Machiry, Rohan Tahiliani, and Mayur Naik · 2013
Earlier work this paper cites.
Capture-replay testing for android applications
Chien Hung Liu, Chien Yu Lu, Shan Jen Cheng, Koan Yuh Chang, Yung Chia Hsiao, and Weng Ming Chu · 2014
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Sapienz: Multi-objective automated testing for android applications
Ke Mao, Mark Harman, and Yue Jia · 2016
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Droidbot: A lightweight ui-guided test input generator for android
Yuanchun Li, Ziyue Yang, Yao Guo, and Xiangqun Chen · 2017
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World of bits: An open-domain platform for web-based agents
Tianlin Shi, Andrej Karpathy, Linxi Fan, Jonathan Hernandez, and Percy Liang · 2017
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An empirical study of android test generation tools in industrial cases
Wenyu Wang, Dengfeng Li, Wei Yang, Yurui Cao, Zhenwen Zhang, Yuetang Deng, and Tao Xie · 2018
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Guiding app testing with mined interaction models
Nataniel P. Borges, Maria Gómez, and Andreas Zeller · 2018
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Mapping natural language commands to web elements
Panupong Pasupat, Tian-Shun Jiang, Evan Zheran Liu, Kelvin Guu, and Percy Liang · 2018
Cited alongside, same era.
Humanoid: A deep learning-based approach to automated black-box android app testing
Yuanchun Li, Ziyue Yang, Yao Guo, and Xiangqun Chen · 2019
Cited alongside, same era.
Mapping natural language instructions to mobile UI action sequences
Yang Li, Jiacong He, Xin Zhou, Yuan Zhang, and Jason Baldridge · 2020
Cited alongside, same era.
Mapping natural language instructions to mobile ui action sequences
Yang Li, Jiacong He, Xin Zhou, Yuan Zhang, and Jason Baldridge · 2020
Cited alongside, same era.
Search-based test generation for android apps
Iván Arcuschin Moreno · 2020
Cited alongside, same era.
Glider: A reinforcement learning approach to extract UI scripts from websites
MOTIF: A large malware reference dataset with ground truth family labels
Robert J Joyce, Dev Amlani, Charles Nicholas, and Edward Raff · 2022
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A dataset for interactive vision language navigation with unknown command feasibility
Andrea Burns, Deniz Arsan, Sanjna Agrawal, Ranjitha Kumar, Kate Saenko, and Bryan A. Plummer · 2022
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Bloomberggpt: A large language model for finance
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann · 2023
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An exploratory survey about using chatgpt in education, healthcare, and research
Mohammad Hosseini, Catherine A. Gao, David M. Liebovitz, Alexandre M. Carvalho, Faraz S. Ahmad, Yuan Luo, Ngan MacDonald, Kristi L. Holmes, and Abel Kho · 2023
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Grounded decoding: Guiding text generation with grounded models for robot control, 2023
Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, and Brian Ichter · 2023
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Yuanchun Li and Oriana Riva · 2021
Cited alongside, same era.
Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, and John Schulman · 2021
Cited alongside, same era.
Ui/application exerciser monkey
Android Developers
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Lexi: Self-supervised learning of the ui language, 2023
Pratyay Banerjee, Shweti Mahajan, Kushal Arora, Chitta Baral, and Oriana Riva · 2023
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Screen correspondence: Mapping interchangeable elements between uis, 2023
Jason Wu, Amanda Swearngin, Xiaoyi Zhang, Jeffrey Nichols, and Jeffrey P. Bigham · 2023
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