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Performing complex tasks in open environments remains challenging for robots, even when using large language models (LLMs) as the core planner.
Language models are few-shot learners
Brown, T. B. (2020) · 2005
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ARM Architecture Reference Manual, ARMv8
ARM Limited (2013) · 2013
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On evaluation of embodied navigation agents
Anderson, P., Chang, A., Chaplot, D. S., Dosovitskiy, A., Gupta, S., Koltun, V., Kosecka, J., Malik, J., Mottaghi, R., Savva, M., et al. (2018) · 2018
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Intel ® 64 and IA-32 Architectures Software Developer’s Manual
Intel Corporation (2021) · 2021
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Do as i can, not as i say: Grounding language in robotic affordances
Ahn, M., Brohan, A., Brown, N., Chebotar, Y., Cortes, O., David, B., Finn, C., Fu, C., Gopalakrishnan, K., Hausman, K., et al. (2022) · 2022
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Rt-1: Robotics transformer for real-world control at scale
Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Dabis, J., Finn, C., Gopalakrishnan, K., Hausman, K., Herzog, A., Hsu, J., et al. (2022) · 2022
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Large language models are reasoning teachers
Ho, N., Schmid, L., and Yun, S.-Y. (2022) · 2022
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Rt-2: Vision-language-action models transfer web knowledge to robotic control
Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Chen, X., Choromanski, K., Ding, T., Driess, D., Dubey, A., Finn, C., et al. (2023) · 2023
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Palm-e: An embodied multimodal language model
Driess, D., Xia, F., Sajjadi, M. S., Lynch, C., Chowdhery, A., Ichter, B., Wahid, A., Tompson, J., Vuong, Q., Yu, T., et al. (2023) · 2023
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Anygrasp: Robust and efficient grasp perception in spatial and temporal domains
Fang, H.-S., Wang, C., Fang, H., Gou, M., Liu, J., Yan, H., Liu, W., Xie, Y., and Lu, C. (2023) · 2023
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Smart-llm: Smart multi-agent robot task planning using large language models
Kannan, S. S., Venkatesh, V. L., and Min, B.-C. (2023) · 2023
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Vision-language foundation models as effective robot imitators
Li, X., Liu, M., Zhang, H., Yu, C., Xu, J., Wu, H., Cheang, C., Jing, Y., Zhang, W., Liu, H., Li, H., and Kong, T. (2023) · 2023
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Code as policies: Language model programs for embodied control
Liang, J., Huang, W., Xia, F., Xu, P., Hausman, K., Ichter, B., Florence, P., and Zeng, A. (2023) · 2023
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Taskbench: Benchmarking large language models for task automation
Shen, Y., Song, K., Tan, X., Zhang, W., Ren, K., Yuan, S., Lu, W., Li, D., and Zhuang, Y. (2023) · 2023
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Llama: Open and efficient foundation language models
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., et al. (2023) · 2023
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Ye, Y., Hui, B., Yang, M., Li, B., Huang, F., and Li, Y. (2023) · 2023
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π 0 \pi_{0} : A vision-language-action flow model for general robot control
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Replan: Robotic replanning with perception and language models
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Copal: corrective planning of robot actions with large language models
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