Quan Vuong

2.1k total citations
15 papers, 124 citations indexed

About

Quan Vuong is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Quan Vuong has authored 15 papers receiving a total of 124 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 3 papers in Control and Systems Engineering and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Quan Vuong's work include Reinforcement Learning in Robotics (6 papers), Robot Manipulation and Learning (3 papers) and Machine Learning and Algorithms (2 papers). Quan Vuong is often cited by papers focused on Reinforcement Learning in Robotics (6 papers), Robot Manipulation and Learning (3 papers) and Machine Learning and Algorithms (2 papers). Quan Vuong collaborates with scholars based in United States, Switzerland and China. Quan Vuong's co-authors include Dorsa Sadigh, Ted Xiao, Debidatta Dwibedi, Pierre Sermanet, Yevgen Chebotar, Sergey Levine, Tianli Ding, Jonathan Tompson, Suneel Belkhale and Chelsea Finn and has published in prestigious journals such as arXiv (Cornell University), White Rose Research Online (University of Leeds, The University of Sheffield, University of York) and Neural Information Processing Systems.

In The Last Decade

Quan Vuong

15 papers receiving 119 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Quan Vuong United States	7	52	49	47	10	7	15	124
Suneel Belkhale United States	4	48 0.9×	38 0.8×	39 0.8×	8 0.8×	5 0.7×	4	113
Bradly C. Stadie United States	5	124 2.4×	57 1.2×	65 1.4×	9 0.9×	4 0.6×	9	177
Murtaza Dalal United States	3	74 1.4×	27 0.6×	35 0.7×	9 0.9×	4 0.6×	4	102
Giuseppe Cuccu Switzerland	7	118 2.3×	35 0.7×	20 0.4×	17 1.7×	5 0.7×	15	165
Manuel Watter Germany	2	82 1.6×	53 1.1×	32 0.7×	7 0.7×	1 0.1×	3	133
János Kramár United Kingdom	4	90 1.7×	43 0.9×	80 1.7×	6 0.6×	10 1.4×	8	152
Paul Szerlip United States	7	73 1.4×	40 0.8×	10 0.2×	18 1.8×	5 0.7×	13	147
Soroush Nasiriany United States	5	52 1.0×	30 0.6×	55 1.2×	3 0.3×	6 0.9×	9	107
Ted Xiao United States	3	30 0.6×	26 0.5×	50 1.1×	12 1.2×	1 0.1×	7	79
Riad Akrour Germany	8	93 1.8×	28 0.6×	56 1.2×	13 1.3×	5 0.7×	13	139

Countries citing papers authored by Quan Vuong

Since Specialization

Citations

This map shows the geographic impact of Quan Vuong's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Quan Vuong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quan Vuong more than expected).

Fields of papers citing papers by Quan Vuong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Quan Vuong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Quan Vuong. The network helps show where Quan Vuong may publish in the future.

Co-authorship network of co-authors of Quan Vuong

This figure shows the co-authorship network connecting the top 25 collaborators of Quan Vuong. A scholar is included among the top collaborators of Quan Vuong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Quan Vuong. Quan Vuong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

1.

Pertsch, Karl, Brian Ichter, Danny Driess, et al.. (2025). FAST: Efficient Action Tokenization for Vision-Language-Action Models. 6 indexed citations

2.

Walke, Homer, Karl Pertsch, Kevin Black, et al.. (2024). Octo: An Open-Source Generalist Robot Policy. 29 indexed citations

3.

Xiao, Ted, Sumeet Singh, Quan Vuong, et al.. (2024). How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies. 4340–4348. 8 indexed citations

4.

Singh, Anikait, et al.. (2024). Robotic Offline RL from Internet Videos via Value-Function Learning. 16977–16984. 2 indexed citations

5.

Leal, Isabel, Krzysztof Choromański, Deepali Jain, et al.. (2024). SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. 6920–6927. 5 indexed citations

6.

Shah, Dhruv, et al.. (2024). Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation. arXiv (Cornell University). 7 indexed citations

7.

Belkhale, Suneel, Tianli Ding, Ted Xiao, et al.. (2024). RT-H: Action Hierarchies using Language. 25 indexed citations

8.

Chen, Lawrence R., et al.. (2024). MIRAGE: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting. 5 indexed citations

9.

Joshi, Nikhil, Ayzaan Wahid, Danny Driess, et al.. (2024). Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers. 11 indexed citations

10.

Wang, Luobin, et al.. (2023). A Real2Sim2Real Method for Robust Object Grasping with Neural Surface Reconstruction. 1–8. 7 indexed citations

11.

Zhang, Yiming, Quan Vuong, & Keith W. Ross. (2020). First Order Constrained Optimization in Policy Space. Neural Information Processing Systems. 33. 15338–15349. 2 indexed citations

12.

Vuong, Quan, et al.. (2019). Better Exploration with Optimistic Actor-Critic. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 32. 1787–1798. 9 indexed citations

13.

Zhang, Yiming, et al.. (2018). Efficient entropy for policy gradient with multi-dimensional action space. arXiv (Cornell University). 4 indexed citations

14.

Vuong, Quan, Yiming Zhang, & Keith W. Ross. (2018). Supervised Policy Update for Deep Reinforcement Learning. arXiv (Cornell University). 1 indexed citations

15.

Vuong, Quan, Ha Manh Tran, & Son Thanh Le. (2015). Distributed Event Monitoring for Software Defined Networks. 52. 90–97. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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