Shixiang Gu

11.4k total citations · 2 hit papers
26 papers, 1.6k citations indexed

About

Shixiang Gu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Shixiang Gu has authored 26 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Signal Processing. Recurrent topics in Shixiang Gu's work include Reinforcement Learning in Robotics (14 papers), Adversarial Robustness in Machine Learning (5 papers) and Music and Audio Processing (4 papers). Shixiang Gu is often cited by papers focused on Reinforcement Learning in Robotics (14 papers), Adversarial Robustness in Machine Learning (5 papers) and Music and Audio Processing (4 papers). Shixiang Gu collaborates with scholars based in United States, Germany and United Kingdom. Shixiang Gu's co-authors include Sergey Levine, Timothy Lillicrap, Richard E. Turner, Ilya Sutskever, Zoubin Ghahramani, Ofir Nachum, Honglak Lee, Luca Rigazio, Eric Jang and Ben Poole and has published in prestigious journals such as IEEE Robotics and Automation Letters, Advanced Robotics and Apollo (University of Cambridge).

In The Last Decade

Shixiang Gu

26 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates

2017 829 citations Shixiang Gu, Timothy Lillicrap et al. profile →
Large Language Models Can Self-Improve

2023 107 citations Jiaxin Huang, Shixiang Gu et al. profile →

Peers

Countries citing papers authored by Shixiang Gu

Since Specialization

Citations

This map shows the geographic impact of Shixiang Gu'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 Shixiang Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shixiang Gu more than expected).

Fields of papers citing papers by Shixiang Gu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shixiang Gu. 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 Shixiang Gu. The network helps show where Shixiang Gu may publish in the future.

Co-authorship network of co-authors of Shixiang Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Shixiang Gu. A scholar is included among the top collaborators of Shixiang Gu 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 Shixiang Gu. Shixiang Gu 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:

20 of 20 papers shown

#	Work	Indexed citations
1	Large Language Models Can Self-Improve breakdown → 2023 ·Jiaxin Huang, Shixiang Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han	107
2	Collective Intelligence for 2D Push Manipulations With Mobile Robots 2023 ·IEEE Robotics and Automation Letters ·(unknown), (unknown), (unknown), (unknown), Yutaka Matsuo, Shixiang Gu, (unknown)	3
3	Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains 2023 ·Transactions of the Japanese Society for Artificial Intelligence ·(unknown), Shixiang Gu, Yutaka Matsuo, Yusuke Iwasawa	9
4	World robot challenge 2020 – partner robot: a data-driven approach for room tidying with mobile manipulator 2022 ·Advanced Robotics ·(unknown), Yuki Noguchi, (unknown), (unknown), (unknown), (unknown), (unknown), Shohei Taniguchi, Yūki Yamashita, (unknown), Shixiang Gu, Yusuke Iwasawa, Yutaka Matsuo	8
5	Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning 2021 ·International Conference on Machine Learning ·Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Gu	2
6	EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL 2021 ·International Conference on Machine Learning ·Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Gu	11
7	Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization 2021 ·International Conference on Learning Representations ·(unknown), (unknown), Yutaka Matsuo, Ofir Nachum, Shixiang Gu	1
8	Dynamics-Aware Unsupervised Skill Discovery 2020 ·International Conference on Learning Representations ·Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman	3
9	Language as an Abstraction for Hierarchical Deep Reinforcement Learning 2019 ·Neural Information Processing Systems ·Yiding Jiang, Shixiang Gu, Kevin P. Murphy, Chelsea Finn	8
10	SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies 2019 ·Neural Information Processing Systems ·Seyed Kamyar Seyed Ghasemipour, Shixiang Gu, Richard S. Zemel	10
11	Temporal Difference Models: Model-Free Deep RL for Model-Based Control 2018 ·MPG.PuRe (Max Planck Society) ·Vitchyr H. Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine	57
12	Data-Efficient Hierarchical Reinforcement Learning 2018 ·arXiv (Cornell University) ·Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine	109
13	Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control 2017 ·Apollo (University of Cambridge) ·Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, José Miguel Hernández-Lobato, Richard E. Turner, Douglas Eck	39
14	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning Shixiang 2017 ·Apollo (University of Cambridge) ·Shixiang Gu, Timothy Lillicrap, Zoubin Ghahramani, Richard E. Turner, Bernhard Schölkopf, Sergey Levine	37
15	Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates breakdown → 2017 ·Shixiang Gu, (unknown), Timothy Lillicrap, Sergey Levine	829
16	Q-PrOP: Sample-efficient policy gradient with an off-policy critic 2017 ·Apollo (University of Cambridge) ·Shixiang Gu, Timothy Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine	70
17	Tuning Recurrent Neural Networks with Reinforcement Learning 2016 ·arXiv (Cornell University) ·Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck	24
18	Continuous Deep Q-Learning with Model-based Acceleration 2016 ·arXiv (Cornell University) ·Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine	155
19	Neural Adaptive Sequential Monte Carlo 2015 ·Apollo (University of Cambridge) ·Shixiang Gu, Zoubin Ghahramani, Richard E. Turner	19
20	Towards Deep Neural Network Architectures Robust to Adversarial Examples 2014 ·International Conference on Learning Representations ·Shixiang Gu, Luca Rigazio	46

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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