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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:

Learning to push by grasping: Using multiple tasks for effective learning
Lerrel Pinto, Abhinav Gupta
(2017), pp. 2161-2168
Open Access | Times Cited: 107

Showing 1-25 of 107 citing articles:

Multi-task Self-Supervised Visual Learning
Carl Doersch, Andrew Zisserman
(2017)
Open Access | Times Cited: 586
Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning
Andy Zeng, Shuran Song, Stefan Welker, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018)
Open Access | Times Cited: 524
Multi-Task Learning with Deep Neural Networks: A Survey
Michael Crawshaw
arXiv (Cornell University) (2020)
Open Access | Times Cited: 346
Learning to fly by crashing
Dhiraj Gandhi, Lerrel Pinto, Abhinav Gupta
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2017)
Closed Access | Times Cited: 243
Asymmetric Actor Critic for Image-Based Robot Learning
Lerrel Pinto, Marcin Andrychowicz, Peter Welinder, et al.
(2018)
Open Access | Times Cited: 209
Cross-Domain Self-Supervised Multi-task Feature Learning Using Synthetic Imagery
Zhongzheng Ren, Yong Jae Lee
(2018)
Open Access | Times Cited: 201
Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-to-End Learning from Demonstration
Rouhollah Rahmatizadeh, Pooya Abolghasemi, Ladislau Bölöni, et al.
(2018), pp. 3758-3765
Open Access | Times Cited: 185
Grasping in the Wild: Learning 6DoF Closed-Loop Grasping From Low-Cost Demonstrations
Shuran Song, Andy Zeng, Johnny Lee, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 3, pp. 4978-4985
Open Access | Times Cited: 140
RoboAgent: Generalization and Efficiency in Robot Manipulation via Semantic Augmentations and Action Chunking
Homanga Bharadhwaj, Jay Vakil, Mohit Sharma, et al.
(2024), pp. 4788-4795
Open Access | Times Cited: 15
Toward Robotic Manipulation
Matthew T. Mason
Annual Review of Control Robotics and Autonomous Systems (2018) Vol. 1, Iss. 1, pp. 1-28
Open Access | Times Cited: 134
Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition
Unaiza Ahsan, Rishi Madhok, Irfan Essa
(2019), pp. 179-189
Open Access | Times Cited: 106
A Deep Learning Approach to Grasping the Invisible
Yang Yang, Hengyue Liang, Changhyun Choi
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 2, pp. 2232-2239
Open Access | Times Cited: 89
What Should Not Be Contrastive in Contrastive Learning
Tete Xiao, Xiao-Long Wang, Alexei A. Efros, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 84
Review of Deep Reinforcement Learning-Based Object Grasping: Techniques, Open Challenges, and Recommendations
Marwan Qaid Mohammed, Lee Chung Kwek, Shing Chyi Chua
IEEE Access (2020) Vol. 8, pp. 178450-178481
Open Access | Times Cited: 81
Where2Act: From Pixels to Actions for Articulated 3D Objects
Kaichun Mo, Leonidas Guibas, Mustafa Mukadam, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021), pp. 6793-6803
Open Access | Times Cited: 81
DensePhysNet: Learning Dense Physical Object Representations Via Multi-Step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng, et al.
(2019)
Open Access | Times Cited: 75
Multi-task Self-Supervised Visual Learning
Carl Doersch, Andrew Zisserman
arXiv (Cornell University) (2017)
Closed Access | Times Cited: 62
Visual Manipulation Relationship Network for Autonomous Robotics
Hanbo Zhang, Xuguang Lan, Xinwen Zhou, et al.
(2018), pp. 118-125
Closed Access | Times Cited: 59
What Should Not Be Contrastive in Contrastive Learning
Tete Xiao, Xiaolong Wang, Alexei A. Efros, et al.
(2021)
Closed Access | Times Cited: 51
Learning Actionable Representations from Visual Observations
Debidatta Dwibedi, Jonathan Tompson, Corey Lynch, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018), pp. 1577-1584
Open Access | Times Cited: 53
Multi-Task Reinforcement Learning with Soft Modularization
Ruihan Yang, Huazhe Xu, Yi Wu, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 46
Curiosity-Driven Experience Prioritization via Density Estimation
Rui Zhao, Volker Tresp
arXiv (Cornell University) (2019)
Open Access | Times Cited: 45
Grasping Unknown Objects by Coupling Deep Reinforcement Learning, Generative Adversarial Networks, and Visual Servoing
Ole-Magnus Pedersen, Ekrem Misimi, François Chaumette
(2020)
Open Access | Times Cited: 36
Prehensile and Non-Prehensile Robotic Pick-and-Place of Objects in Clutter Using Deep Reinforcement Learning
Muhammad Babar Imtiaz, Yuansong Qiao, Brian Lee
Sensors (2023) Vol. 23, Iss. 3, pp. 1513-1513
Open Access | Times Cited: 11
CASSL: Curriculum Accelerated Self-Supervised Learning
Adithyavairavan Murali, Lerrel Pinto, Dhiraj Gandhi, et al.
(2018), pp. 6453-6460
Open Access | Times Cited: 33
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