GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration

Language models are few-shot learners

Original

Tom B Brown. 2020 · 2005

Earlier work this paper cites.

Thinking, fast and slow

Daniel Kahneman. 2011 · 2011

Earlier work this paper cites.

Data distributional properties drive emergent in-context learning in transformers

Stephanie Chan, Adam Santoro, Andrew Lampinen, Jane Wang, Aaditya Singh, Pierre Richemond, James McClelland, and Felix Hill. 2022 · 2022

Earlier work this paper cites.

What can transformers learn in-context? a case study of simple function classes

Shivam Garg, Dimitris Tsipras, Percy S Liang, and Gregory Valiant. 2022 · 2022

Earlier work this paper cites.

In-context reinforcement learning with algorithm distillation

Original

Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, et al. 2022 · 2022

Earlier work this paper cites.

Prompting decision transformer for few-shot policy generalization

Mengdi Xu, Yikang Shen, Shun Zhang, Yuchen Lu, Ding Zhao, Joshua Tenenbaum, and Chuang Gan. 2022 · 2022

Earlier work this paper cites.

Qwen-vl: A frontier large vision-language model with versatile abilities

Original

Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou. 2023 · 2023

Earlier work this paper cites.

Mind2web: Towards a generalist agent for the web

Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samuel Stevens, Boshi Wang, Huan Sun, and Yu Su. 2023 · 2023

Earlier work this paper cites.

What in-context learning “learns” in-context: Disentangling task recognition and task learning

Jane Pan. 2023 · 2023

Earlier work this paper cites.

Label words are anchors: An information flow perspective for understanding in-context learning

Original

Lean Wang, Lei Li, Damai Dai, Deli Chen, Hao Zhou, Fandong Meng, Jie Zhou, and Xu Sun. 2023 · 2023

Earlier work this paper cites.

Larger language models do in-context learning differently

Original

Jerry Wei, Jason Wei, Yi Tay, Dustin Tran, Albert Webson, Yifeng Lu, Xinyun Chen, Hanxiao Liu, Da Huang, Denny Zhou, et al. 2023 · 2023

Cited alongside, same era.

Set-of-mark prompting unleashes extraordinary visual grounding in gpt-4v

Original

Jianwei Yang, Hao Zhang, Feng Li, Xueyan Zou, Chunyuan Li, and Jianfeng Gao. 2023 · 2023

Cited alongside, same era.

Webarena: A realistic web environment for building autonomous agents

Original

Shuyan Zhou, Frank F Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, et al. 2023 · 2023

Cited alongside, same era.

Agent s: An open agentic framework that uses computers like a human

Original

Saaket Agashe, Jiuzhou Han, Shuyu Gan, Jiachen Yang, Ang Li, and Xin Eric Wang. 2024 · 2024

Cited alongside, same era.

Llava-next: Stronger llms supercharge multimodal capabilities in the wild

Bo Li, Kaichen Zhang, Hao Zhang, Dong Guo, Renrui Zhang, Feng Li, Yuanhan Zhang, Ziwei Liu, and Chunyuan Li. 2024 · 2024

Later among the works it cites.

Showui: One vision-language-action model for gui visual agent

Original

Kevin Qinghong Lin, Linjie Li, Difei Gao, Zhengyuan Yang, Shiwei Wu, Zechen Bai, Weixian Lei, Lijuan Wang, and Mike Zheng Shou. 2024 · 2024

Later among the works it cites.

Harnessing webpage uis for text-rich visual understanding

Original

Junpeng Liu, Tianyue Ou, Yifan Song, Yuxiao Qu, Wai Lam, Chenyan Xiong, Wenhu Chen, Graham Neubig, and Xiang Yue. 2024 · 2024

Later among the works it cites.

Omniparser for pure vision based gui agent

Original

Yadong Lu, Jianwei Yang, Yelong Shen, and Ahmed Awadallah. 2024 · 2024

Later among the works it cites.

Llms are in-context reinforcement learners