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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:

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Tianhe Yu, Deirdre Quillen, Zhanpeng He, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 247

Showing 1-25 of 247 citing articles:

Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales, Antreas Antoniou, Paul Micaelli, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021), pp. 1-1
Open Access | Times Cited: 1303
Multi-Task Learning with Deep Neural Networks: A Survey
Michael Crawshaw
arXiv (Cornell University) (2020)
Open Access | Times Cited: 345
Embracing Change: Continual Learning in Deep Neural Networks
Raia Hadsell, Dushyant Rao, Andrei A. Rusu, et al.
Trends in Cognitive Sciences (2020) Vol. 24, Iss. 12, pp. 1028-1040
Open Access | Times Cited: 317
A survey of deep meta-learning
Mike Huisman, Jan N. van Rijn, Aske Plaat
Artificial Intelligence Review (2021) Vol. 54, Iss. 6, pp. 4483-4541
Open Access | Times Cited: 296
RLBench: The Robot Learning Benchmark & Learning Environment
Stephen James, Zicong Ma, David Rovick Arrojo, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 2, pp. 3019-3026
Closed Access | Times Cited: 193
A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution
Akhil Hannegudda Ganesh, Bin Xu
Renewable and Sustainable Energy Reviews (2021) Vol. 154, pp. 111833-111833
Closed Access | Times Cited: 178
Deep reinforcement learning in computer vision: a comprehensive survey
Ngan Le, Vidhiwar Singh Rathour, Kashu Yamazaki, et al.
Artificial Intelligence Review (2021) Vol. 55, Iss. 4, pp. 2733-2819
Open Access | Times Cited: 155
RT-1: Robotics Transformer for Real-World Control at Scale
Anthony Brohan, Noah Brown, Justice Carbajal, et al.
(2023)
Open Access | Times Cited: 154
dm_control: Software and tasks for continuous control
Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, et al.
Software Impacts (2020) Vol. 6, pp. 100022-100022
Open Access | Times Cited: 152
Deep reinforcement learning in medical imaging: A literature review
S. Kevin Zhou, Ngan Le, Khoa Luu, et al.
Medical Image Analysis (2021) Vol. 73, pp. 102193-102193
Open Access | Times Cited: 146
Towards Continual Reinforcement Learning: A Review and Perspectives
Khimya Khetarpal, Matthew Riemer, Irina Rish, et al.
Journal of Artificial Intelligence Research (2022) Vol. 75, pp. 1401-1476
Open Access | Times Cited: 112
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 78
A Survey of Zero-shot Generalisation in Deep Reinforcement Learning
Robert Kirk, Amy Zhang, Edward Grefenstette, et al.
Journal of Artificial Intelligence Research (2023) Vol. 76, pp. 201-264
Open Access | Times Cited: 72
Half a Dozen Real-World Applications of Evolutionary Multitasking, and More
Abhishek Gupta, Lei Zhou, Yew-Soon Ong, et al.
IEEE Computational Intelligence Magazine (2022) Vol. 17, Iss. 2, pp. 49-66
Open Access | Times Cited: 68
Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments
Mayank Mittal, Calvin Yu, Qinxi Yu, et al.
IEEE Robotics and Automation Letters (2023) Vol. 8, Iss. 6, pp. 3740-3747
Open Access | Times Cited: 43
Advances and Challenges in Meta-Learning: A Technical Review
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Joaquin Vanschoren, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 7, pp. 4763-4779
Open Access | Times Cited: 39
Self-Driving Laboratories for Chemistry and Materials Science
Gary Tom, Stefan P. Schmid, Sterling G. Baird, et al.
Chemical Reviews (2024) Vol. 124, Iss. 16, pp. 9633-9732
Open Access | Times Cited: 31
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Ilya Kostrikov, Denis Yarats, Rob Fergus
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 116
iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes
Bokui Shen, Fei Xia, Chengshu Li, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2021)
Open Access | Times Cited: 98
Gradient Surgery for Multi-Task Learning
Tianhe Yu, Saurabh Kumar, Abhishek Gupta, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 94
CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP
Qinyuan Ye, Bill Yuchen Lin, Xiang Ren
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
Open Access | Times Cited: 92
Teaching robots to perform quasi-repetitive construction tasks through human demonstration
Ci-Jyun Liang, Vineet R. Kamat, Carol C. Menassa
Automation in Construction (2020) Vol. 120, pp. 103370-103370
Closed Access | Times Cited: 82
Visual Room Rearrangement
Luca Weihs, Matt Deitke, Aniruddha Kembhavi, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Open Access | Times Cited: 67
Conflict-Averse Gradient Descent for Multi-task Learning
Bo Liu, Xingchao Liu, Xiaojie Jin, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 64
ManipulaTHOR: A Framework for Visual Object Manipulation
Kiana Ehsani, Winson Han, Alvaro Herrasti, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Open Access | Times Cited: 59
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