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Autonomous agents powered by large language models (LLMs) have the potential to enhance human capabilities, assisting with digital tasks from sending emails to performing data analysis.
Efficient selectivity and backup operators in monte-carlo tree search
R. Coulom · 2006
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Bandit based monte-carlo planning
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Data-efficient off-policy policy evaluation for reinforcement learning
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Data-efficient hierarchical reinforcement learning
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Mapping natural language instructions to mobile ui action sequences
Y. Li, J. He, X. Zhou, Y. Zhang, and J. Baldridge · 2020
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Data-efficient reinforcement learning with self-predictive representations
M. Schwarzer, A. Anand, R. Goel, R. D. Hjelm, A. Courville, and P. Bachman · 2020
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Lora: Low-rank adaptation of large language models
E. J. Hu, Y. Shen, P. Wallis, Z. Allen-Zhu, Y. Li, S. Wang, L. Wang, and W. Chen · 2021
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Pretraining representations for data-efficient reinforcement learning
M. Schwarzer, N. Rajkumar, M. Noukhovitch, A. Anand, L. Charlin, R. D. Hjelm, P. Bachman, and A. C. Courville · 2021
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Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
W. Huang, P. Abbeel, D. Pathak, and I. Mordatch · 2022
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Physical interaction and manipulation of the environment using aerial robots
A. Keipour · 2022
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Selective annotation makes language models better few-shot learners
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J. Achiam, S. Adler, S. Agarwal, L. Ahmad, I. Akkaya, F. L. Aleman, D. Almeida, J. Altenschmidt, S. Altman, S. Anadkat, et al · 2023
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Rest meets react: Self-improvement for multi-step reasoning llm agent
R. Aksitov, S. Miryoosefi, Z. Li, D. Li, S. Babayan, K. Kopparapu, Z. Fisher, R. Guo, S. Prakash, P. Srinivasan, et al · 2023
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Efficient online reinforcement learning with offline data
P. J. Ball, L. Smith, I. Kostrikov, and S. Levine · 2023
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Fireact: Toward language agent fine-tuning
B. Chen, C. Shu, E. Shareghi, N. Collier, K. Narasimhan, and S. Yao · 2023
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Reinforced self-training (rest) for language modeling
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A real-world webagent with planning, long context understanding, and program synthesis
I. Gur, H. Furuta, A. Huang, M. Safdari, Y. Matsuo, D. Eck, and A. Faust · 2023
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Swe-bench: Can language models resolve real-world github issues?
Introducing claude 3.5 sonnet, 2024
Anthropic · 2024
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Spider2-v: How far are multimodal agents from automating data science and engineering workflows?
R. Cao, F. Lei, H. Wu, J. Chen, Y. Fu, H. Gao, X. Xiong, H. Zhang, Y. Mao, W. Hu, et al · 2024
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Mind2web: Towards a generalist agent for the web
X. Deng, Y. Gu, B. Zheng, S. Chen, S. Stevens, B. Wang, H. Sun, and Y. Su · 2024
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WorkArena: How capable are web agents at solving common knowledge work tasks?
A. Drouin, M. Gasse, M. Caccia, I. H. Laradji, M. Del Verme, T. Marty, D. Vazquez, N. Chapados, and A. Lacoste · 2024
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M. Hu, P. Zhao, C. Xu, Q. Sun, J. Lou, Q. Lin, P. Luo, S. Rajmohan, and D. Zhang · 2024
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C. E. Jimenez, J. Yang, A. Wettig, S. Yao, K. Pei, O. Press, and K. Narasimhan · 2023
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On learning to summarize with large language models as references
Y. Liu, K. Shi, K. S. He, L. Ye, A. R. Fabbri, P. Liu, D. Radev, and A. Cohan · 2023
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Summarization is (almost) dead
X. Pu, M. Gao, and X. Wan · 2023
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Openagents: An open platform for language agents in the wild
T. Xie, F. Zhou, Z. Cheng, P. Shi, L. Weng, Y. Liu, T. J. Hua, J. Zhao, Q. Liu, C. Liu, et al · 2023
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Appagent: Multimodal agents as smartphone users
Z. Yang, J. Liu, Y. Han, X. Chen, Z. Huang, B. Fu, and G. Yu · 2023
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Lumos: Learning agents with unified data, modular design, and open-source llms
D. Yin, F. Brahman, A. Ravichander, K. Chandu, K.-W. Chang, Y. Choi, and B. Y. Lin · 2023
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Agenttuning: Enabling generalized agent abilities for llms
A. Zeng, M. Liu, R. Lu, B. Wang, X. Liu, Y. Dong, and J. Tang · 2023
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You only look at screens: Multimodal chain-of-action agents
Z. Zhan and A. Zhang · 2023
Cited alongside, same era.
Visualwebarena: Evaluating multimodal agents on realistic visual web tasks
J. Y. Koh, R. Lo, L. Jang, V. Duvvur, M. C. Lim, P.-Y. Huang, G. Neubig, S. Zhou, R. Salakhutdinov, and D. Fried · 2024
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Self-refine: Iterative refinement with self-feedback
A. Madaan, N. Tandon, P. Gupta, S. Hallinan, L. Gao, S. Wiegreffe, U. Alon, N. Dziri, S. Prabhumoye, Y. Yang, et al · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M. Reid, N. Savinov, D. Teplyashin, D. Lepikhin, T. Lillicrap, J.-b. Alayrac, R. Soricut, A. Lazaridou, O. Firat, J. Schrittwieser, et al · 2024
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Reflexion: Language agents with verbal reinforcement learning
N. Shinn, F. Cassano, A. Gopinath, K. Narasimhan, and S. Yao · 2024
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Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments
T. Xie, D. Zhang, J. Chen, X. Li, S. Zhao, R. Cao, T. J. Hua, Z. Cheng, D. Shin, F. Lei, et al · 2024
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Swe-agent: Agent-computer interfaces enable automated software engineering
J. Yang, C. E. Jimenez, A. Wettig, K. Lieret, S. Yao, K. Narasimhan, and O. Press · 2024
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Ui-hawk: Unleashing the screen stream understanding for gui agents
J. Zhang, Y. Yu, M. Liao, W. Li, J. Wu, and Z. Wei · 2024
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Do we really need a complex agent system? distill embodied agent into a single model
Z. Zhao, K. Ma, W. Chai, X. Wang, K. Chen, D. Guo, Y. Zhang, H. Wang, and G. Wang · 2024
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