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The vision of a broadly capable and goal-directed agent, such as an Internet-browsing agent in the digital world and a household humanoid in the physical world, has rapidly advanced, thanks to the generalization capability of foundation models.
Dynamics-aware unsupervised discovery of skills, 2020
Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, and Karol Hausman · 1907
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Explore, discover and learn: Unsupervised discovery of state-covering skills, 2020
Víctor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro i Nieto, and Jordi Torres · 2002
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Language as a cognitive tool to imagine goals in curiosity-driven exploration, 2020
Cédric Colas, Tristan Karch, Nicolas Lair, Jean-Michel Dussoux, Clément Moulin-Frier, Peter Ford Dominey, and Pierre-Yves Oudeyer · 2002
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2005
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Variational option discovery algorithms, 2018
Joshua Achiam, Harrison Edwards, Dario Amodei, and Pieter Abbeel · 2018
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Diversity is all you need: Learning skills without a reward function, 2018
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, and Sergey Levine · 2018
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A real-world webagent with planning, long context understanding, and program synthesis, 2021
Izzeddin Gur, Hiroki Furuta, Austin V. Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, and Aleksandra Faust · 2021
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Unsupervised reinforcement learning with contrastive intrinsic control
Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, and Pieter Abbeel · 2022
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Lipschitz-constrained unsupervised skill discovery, 2022
Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, and Gunhee Kim · 2022
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Fireact: Toward language agent fine-tuning, 2023
Baian Chen, Chang Shu, Ehsan Shareghi, Nigel Collier, Karthik Narasimhan, and Shunyu Yao · 2023
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Augmenting autotelic agents with large language models, 2023
Cédric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer, Xingdi Yuan, and Marc-Alexandre Côté · 2023
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Mind2web: Towards a generalist agent for the web, 2023
Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samuel Stevens, Boshi Wang, Huan Sun, and Yu Su · 2023
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Guiding pretraining in reinforcement learning with large language models, 2023
Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, and Jacob Andreas · 2023
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Controllability-aware unsupervised skill discovery, 2023
Seohong Park, Kimin Lee, Youngwoon Lee, and Pieter Abbeel · 2023
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Offline rl for natural language generation with implicit language q learning, 2023
Charlie Snell, Ilya Kostrikov, Yi Su, Mengjiao Yang, and Sergey Levine · 2023
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Agenttuning: Enabling generalized agent abilities for llms, 2023
Aohan Zeng, Mingdao Liu, Rui Lu, Bowen Wang, Xiao Liu, Yuxiao Dong, and Jie Tang · 2023
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The claude 3 model family: Opus, sonnet, haiku, 2024
Anthropic · 2024
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Digirl: Training in-the-wild device-control agents with autonomous reinforcement learning, 2024
Hao Bai, Yifei Zhou, Mert Cemri, Jiayi Pan, Alane Suhr, Sergey Levine, and Aviral Kumar · 2024
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The llama 3 herd of models, 2024
Llama3Team · 2024
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OpenAI · 2024
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Autonomous evaluation and refinement of digital agents, 2024
Jiayi Pan, Yichi Zhang, Nicholas Tomlin, Yifei Zhou, Sergey Levine, and Alane Suhr · 2024
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Iterative reasoning preference optimization, 2024
Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, and Jason Weston · 2024
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Metra: Scalable unsupervised rl with metric-aware abstraction, 2024
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Maxence Faldor, Jenny Zhang, Antoine Cully, and Jeff Clune · 2024
Cited alongside, same era.
Multimodal web navigation with instruction-finetuned foundation models, 2024
Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo, Aleksandra Faust, Shixiang Shane Gu, and Izzeddin Gur · 2024
Cited alongside, same era.
Gemini: A family of highly capable multimodal models, 2024
GeminiTeam · 2024
Cited alongside, same era.
Webvoyager: Building an end-to-end web agent with large multimodal models, 2024
Hongliang He, Wenlin Yao, Kaixin Ma, Wenhao Yu, Yong Dai, Hongming Zhang, Zhenzhong Lan, and Dong Yu · 2024
Cited alongside, same era.
Mengkang Hu, Pu Zhao, Can Xu, Qingfeng Sun, Jianguang Lou, Qingwei Lin, Ping Luo, Saravan Rajmohan, and Dongmei Zhang · 2024
Cited alongside, same era.
Swe-bench: Can language models resolve real-world github issues?, 2024
Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan · 2024
Cited alongside, same era.
Visualwebarena: Evaluating multimodal agents on realistic visual web tasks, 2024
Jing Yu Koh, Robert Lo, Lawrence Jang, Vikram Duvvur, Ming Chong Lim, Po-Yu Huang, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, and Daniel Fried · 2024
Cited alongside, same era.
Showui: One vision-language-action model for gui visual agent, 2024
Kevin Qinghong Lin, Linjie Li, Difei Gao, Zhengyuan Yang, Shiwei Wu, Zechen Bai, Weixian Lei, Lijuan Wang, and Mike Zheng Shou · 2024
Cited alongside, same era.
Seohong Park, Oleh Rybkin, and Sergey Levine · 2024
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Agent q: Advanced reasoning and learning for autonomous ai agents, 2024
Pranav Putta, Edmund Mills, Naman Garg, Sumeet Motwani, Chelsea Finn, Divyansh Garg, and Rafael Rafailov · 2024
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Webrl: Training llm web agents via self-evolving online curriculum reinforcement learning, 2024
Zehan Qi, Xiao Liu, Iat Long Iong, Hanyu Lai, Xueqiao Sun, Wenyi Zhao, Yu Yang, Xinyue Yang, Jiadai Sun, Shuntian Yao, Tianjie Zhang, Wei Xu, Jie Tang, and Yuxiao Dong · 2024
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Meta-rewarding language models: Self-improving alignment with llm-as-a-meta-judge, 2024
Tianhao Wu, Weizhe Yuan, Olga Golovneva, Jing Xu, Yuandong Tian, Jiantao Jiao, Jason Weston, and Sainbayar Sukhbaatar · 2024
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Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments, 2024
Tianbao Xie, Danyang Zhang, Jixuan Chen, Xiaochuan Li, Siheng Zhao, Ruisheng Cao, Toh Jing Hua, Zhoujun Cheng, Dongchan Shin, Fangyu Lei, Yitao Liu, Yiheng Xu, Shuyan Zhou, Silvio Savarese, Caiming Xiong, Victor Zhong, and Tao Yu · 2024
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Self-rewarding language models, 2024
Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Xian Li, Sainbayar Sukhbaatar, Jing Xu, and Jason Weston · 2024
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Fine-tuning large vision-language models as decision-making agents via reinforcement learning, 2024
Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, and Sergey Levine · 2024
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You only look at screens: Multimodal chain-of-action agents, 2024
Zhuosheng Zhang and Aston Zhang · 2024
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Gpt-4v(ision) is a generalist web agent, if grounded, 2024
Boyuan Zheng, Boyu Gou, Jihyung Kil, Huan Sun, and Yu Su · 2024
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