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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:

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
Michelle A. Lee, Yuke Zhu, Krishnan Srinivasan, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 8943-8950
Open Access | Times Cited: 308

Showing 1-25 of 308 citing articles:

Revisiting Self-Supervised Visual Representation Learning
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
Open Access | Times Cited: 682
How to train your robot with deep reinforcement learning: lessons we have learned
Julian Ibarz, Jie Tan, Chelsea Finn, et al.
The International Journal of Robotics Research (2021) Vol. 40, Iss. 4-5, pp. 698-721
Open Access | Times Cited: 380
Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review
Guoguang Du, Kai Wang, Shiguo Lian, et al.
Artificial Intelligence Review (2020) Vol. 54, Iss. 3, pp. 1677-1734
Open Access | Times Cited: 351
DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation
Mike Lambeta, Po-Wei Chou, Stephen Tian, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 3, pp. 3838-3845
Open Access | Times Cited: 338
Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks
Michelle A. Lee, Yuke Zhu, Peter Zachares, et al.
IEEE Transactions on Robotics (2020) Vol. 36, Iss. 3, pp. 582-596
Open Access | Times Cited: 161
Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks
Roberto Martín-Martín, Michelle A. Lee, Rachel Gardner, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2019), pp. 1010-1017
Open Access | Times Cited: 151
Foundations & Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions
Paul Pu Liang, Amir Zadeh, Louis‐Philippe Morency
ACM Computing Surveys (2024) Vol. 56, Iss. 10, pp. 1-42
Open Access | Times Cited: 21
Variable Compliance Control for Robotic Peg-in-Hole Assembly: A Deep-Reinforcement-Learning Approach
Cristian C. Beltran-Hernandez, Damien Petit, Ixchel G. Ramirez-Alpizar, et al.
Applied Sciences (2020) Vol. 10, Iss. 19, pp. 6923-6923
Open Access | Times Cited: 133
Connecting Touch and Vision via Cross-Modal Prediction
Yunzhu Li, Jun-Yan Zhu, Russ Tedrake, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
Open Access | Times Cited: 102
Event-Driven Visual-Tactile Sensing and Learning for Robots
Tasbolat Taunyazov, Weicong Sng, Brian Y. Lim, et al.
(2020)
Open Access | Times Cited: 88
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
Oliver Kroemer, Scott Niekum, George Konidaris
arXiv (Cornell University) (2019)
Open Access | Times Cited: 80
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry
Siyuan Dong, Devesh K. Jha, Diego Romeres, et al.
(2021), pp. 6437-6443
Open Access | Times Cited: 66
Comprehensive Review on Reaching and Grasping of Objects in Robotics
Marwan Qaid Mohammed, Shing Chyi Chua, Lee Chung Kwek
Robotica (2021) Vol. 39, Iss. 10, pp. 1849-1882
Closed Access | Times Cited: 59
A survey on deep learning and deep reinforcement learning in robotics with a tutorial on deep reinforcement learning
Eduardo F. Morales, Rafael Murrieta-Cid, Israel Becerra, et al.
Intelligent Service Robotics (2021) Vol. 14, Iss. 5, pp. 773-805
Closed Access | Times Cited: 55
CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
Oier Mees, Lukás Hermann, Erick Rosete-Beas, et al.
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 3, pp. 7327-7334
Open Access | Times Cited: 49
Visuo-haptic object perception for robots: an overview
Nicolás Navarro-Guerrero, Sibel Toprak, Josip Josifovski, et al.
Autonomous Robots (2023) Vol. 47, Iss. 4, pp. 377-403
Open Access | Times Cited: 23
Sim2Real Transfer for Reinforcement Learning without Dynamics Randomization
Manuel Kaspar, Juan D. Muñoz Osorio, Jürgen Bock
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2020), pp. 4383-4388
Open Access | Times Cited: 66
Human–robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian Optimization
Loris Roveda, Mauro Magni, Martina Cantoni, et al.
Robotics and Autonomous Systems (2020) Vol. 136, pp. 103711-103711
Open Access | Times Cited: 64
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning
Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, et al.
(2020), pp. 7505-7512
Open Access | Times Cited: 54
Self-Supervised Learning Across Domains
Silvia Bucci, Antonio D’Innocente, Yujun Liao, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021), pp. 1-1
Open Access | Times Cited: 50
ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfer
Ruohan Gao, Zilin Si, Yen‐Yu Chang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 10588-10598
Open Access | Times Cited: 35
A Deep Reinforcement Learning Framework for Control of Robotic Manipulators in Simulated Environments
Carlos Calderón, Roger Sarango, Darwin Castillo, et al.
IEEE Access (2024) Vol. 12, pp. 103133-103161
Open Access | Times Cited: 6
Quickly Inserting Pegs into Uncertain Holes using Multi-view Images and Deep Network Trained on Synthetic Data
Joshua C. Triyonoputro, Weiwei Wan, Kensuke Harada
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2019)
Open Access | Times Cited: 50
Progress and Prospects of Multimodal Fusion Methods in Physical Human–Robot Interaction: A Review
Teng Xue, Weiming Wang, Jin Ma, et al.
IEEE Sensors Journal (2020) Vol. 20, Iss. 18, pp. 10355-10370
Closed Access | Times Cited: 48
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
Kibok Lee, Yian Zhu, Kihyuk Sohn, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 48
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