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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 drive from a world on rails
Dian Chen, Vladlen Koltun, Philipp Krähenbühl
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Open Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

Planning-oriented Autonomous Driving
Yihan Hu, Jiazhi Yang, Li Chen, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
Open Access | Times Cited: 249
TransFuser: Imitation With Transformer-Based Sensor Fusion for Autonomous Driving
Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2022) Vol. 45, Iss. 11, pp. 12878-12895
Open Access | Times Cited: 156
NEAT: Neural Attention Fields for End-to-End Autonomous Driving
Kashyap Chitta, Aditya Prakash, Andreas Geiger
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Open Access | Times Cited: 125
ST-P3: End-to-End Vision-Based Autonomous Driving via Spatial-Temporal Feature Learning
Shengchao Hu, Li Chen, Penghao Wu, et al.
Lecture notes in computer science (2022), pp. 533-549
Closed Access | Times Cited: 89
Learning from All Vehicles
Dian Chen, Philipp Krähenbühl
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)
Closed Access | Times Cited: 87
End-to-End Autonomous Driving: Challenges and Frontiers
Li Chen, Penghao Wu, Kashyap Chitta, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 12, pp. 10164-10183
Open Access | Times Cited: 87
Autonomous driving system: A comprehensive survey
Jingyuan Zhao, Wenyi Zhao, Bo Deng, et al.
Expert Systems with Applications (2023) Vol. 242, pp. 122836-122836
Closed Access | Times Cited: 77
Recent Advancements in End-to-End Autonomous Driving Using Deep Learning: A Survey
Pranav Singh Chib, Pravendra Singh
IEEE Transactions on Intelligent Vehicles (2023) Vol. 9, Iss. 1, pp. 103-118
Open Access | Times Cited: 72
Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles
Jiaxun Cui, Hang Qiu, Dian Chen, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 17231-17241
Open Access | Times Cited: 56
ReasonNet: End-to-End Driving with Temporal and Global Reasoning
Hao Shao, Letian Wang, Ruobing Chen, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 13723-13733
Open Access | Times Cited: 38
ADAPT: Action-aware Driving Caption Transformer
Bu Jin, Xinyu Liu, Yupeng Zheng, et al.
(2023)
Open Access | Times Cited: 30
Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
Xiaosong Jia, Penghao Wu, Li Chen, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 21983-21994
Open Access | Times Cited: 30
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients
Niklas Hanselmann, Katrin Renz, Kashyap Chitta, et al.
Lecture notes in computer science (2022), pp. 335-352
Closed Access | Times Cited: 32
Combining Decision Making and Trajectory Planning for Lane Changing Using Deep Reinforcement Learning
Shurong Li, Chong Wei, Ying Wang
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 23, Iss. 9, pp. 16110-16136
Closed Access | Times Cited: 30
GRI: General Reinforced Imitation and Its Application to Vision-Based Autonomous Driving
Raphael Chekroun, Marin Toromanoff, Sascha Hornauer, et al.
Robotics (2023) Vol. 12, Iss. 5, pp. 127-127
Open Access | Times Cited: 21
Hidden Biases of End-to-End Driving Models
Bernhard Jaeger, Kashyap Chitta, Andreas Geiger
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2023), pp. 8206-8215
Open Access | Times Cited: 21
DriveIRL: Drive in Real Life with Inverse Reinforcement Learning
Tung Phan-Minh, Forbes Howington, Ting-Sheng Chu, et al.
(2023), pp. 1544-1550
Closed Access | Times Cited: 17
DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
Xiaosong Jia, Yulu Gao, Li Chen, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2023), pp. 7919-7929
Open Access | Times Cited: 17
Coaching a Teachable Student
Jimuyang Zhang, Zanming Huang, Eshed Ohn-Bar
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
Open Access | Times Cited: 14
Towards learning-based planning: The nuPlan benchmark for real-world autonomous driving
Napat Karnchanachari, Dimitris Geromichalos, Kok Seang Tan, et al.
(2024), pp. 629-636
Open Access | Times Cited: 4
Knowledge Distillation-Enhanced Behavior Transformer for Decision-Making of Autonomous Driving
Rui Zhao, Yuze Fan, Yun Li, et al.
Sensors (2025) Vol. 25, Iss. 1, pp. 191-191
Open Access
Autonomous Driving System Testing via Diversity-Oriented Driving Scenario Exploration
Xinyu Ji, Lei Xue, Zhijian He, et al.
ACM Transactions on Software Engineering and Methodology (2025)
Closed Access
MMFN: Multi-Modal-Fusion-Net for End-to-End Driving
Qingwen Zhang, Mingkai Tang, Ruoyu Geng, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2022)
Open Access | Times Cited: 17
Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Data Sets, Methods, and Challenges
Vinay Chamola, Amit Chougule, Aishwarya Sam, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 10, pp. 17911-17933
Open Access | Times Cited: 3
Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs
Yiqun Duan, Qiang Zhang, Renjing Xu
(2024), pp. 6798-6805
Open Access | Times Cited: 3
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