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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Generating Executable Action Plans with Environmentally-Aware Language Models
Maitrey Gramopadhye, Daniel Szafir
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2023), pp. 3568-3575
Open Access | Times Cited: 12

Showing 12 citing articles:

A survey on large language model based autonomous agents
Lei Wang, Chen Ma, Xueyang Feng, et al.
Frontiers of Computer Science (2024) Vol. 18, Iss. 6
Open Access | Times Cited: 210
ChatGPT Empowered Long-Step Robot Control in Various Environments: A Case Application
Naoki Wake, Atsushi Kanehira, Kazuhiro Sasabuchi, et al.
IEEE Access (2023) Vol. 11, pp. 95060-95078
Open Access | Times Cited: 47
The rise and potential of large language model based agents: a survey
Zhiheng Xi, Wen-Xiang Chen, Xin Hua Guo, et al.
Science China Information Sciences (2025) Vol. 68, Iss. 2
Closed Access | Times Cited: 6
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)
Vishal Pallagani, Bharath Muppasani, Kaushik Roy, et al.
Proceedings of the International Conference on Automated Planning and Scheduling (2024) Vol. 34, pp. 432-444
Open Access | Times Cited: 14
CoPAL: Corrective Planning of Robot Actions with Large Language Models
Frank Joublin, Antonello Ceravola, А. В. Смирнов, et al.
(2024), pp. 8664-8670
Open Access | Times Cited: 5
Application of Pretrained Large Language Models in Embodied Artificial Intelligence
A. K. Kovalev, Aleksandr I. Panov
Doklady Mathematics (2022) Vol. 106, Iss. S1, pp. S85-S90
Open Access | Times Cited: 17
PRogramAR: Augmented Reality End-User Robot Programming
Bryce Ikeda, Daniel Szafir
ACM Transactions on Human-Robot Interaction (2024) Vol. 13, Iss. 1, pp. 1-20
Open Access | Times Cited: 3
A Survey of Reasoning with Foundation Models
Jiankai Sun, Chuanyang Zheng, Enze Xie, et al.
(2023)
Open Access | Times Cited: 8
Unlocking Robotic Autonomy: A Survey on the Applications of Foundation Models
Dae-Sung Jang, Doo-Hyun Cho, Woo-Cheol Lee, et al.
International Journal of Control Automation and Systems (2024) Vol. 22, Iss. 8, pp. 2341-2384
Closed Access | Times Cited: 2
CAPE: Corrective Actions from Precondition Errors using Large Language Models
Shreyas Sundara Raman, Vanya Cohen, Ifrah Idrees, et al.
(2024), pp. 14070-14077
Open Access | Times Cited: 2
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)
Vishal Pallagani, Kaushik Roy, Bharath Muppasani, et al.
arXiv (Cornell University) (2024)
Open Access | Times Cited: 1
Generative AI Agents in Autonomous Machines: A Safety Perspective
Jason Jabbour, Vijay Janapa Reddi
(2024), pp. 1-13
Open Access | Times Cited: 1
Office-in-the-Loop for Building HVAC Control with Multimodal Foundation Models
T. Sawada, Takaomi Hasegawa, Kiyoko Yokoyama, et al.
(2024), pp. 110-120
Open Access
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