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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:

Into the Unknown: Active Monitoring of Neural Networks
Anna Lukina, Christian Schilling, Thomas A. Henzinger
Lecture notes in computer science (2021), pp. 42-61
Closed Access | Times Cited: 22

Showing 22 citing articles:

Conformal Prediction for STL Runtime Verification
Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, et al.
(2023), pp. 142-153
Open Access | Times Cited: 16
Safety Monitoring of Machine Learning Perception Functions: A Survey
Raúl Ferreira, Joris Guérin, Kévin Delmas, et al.
Computational Intelligence (2025) Vol. 41, Iss. 2
Open Access
Verifying Generalization in Deep Learning
Guy Amir, Osher Maayan, Tom Zelazny, et al.
Lecture notes in computer science (2023), pp. 438-455
Open Access | Times Cited: 7
Learning Monitorable Operational Design Domains for Assured Autonomy
Hazem Torfah, Carol Xie, Sebastian Junges, et al.
Lecture notes in computer science (2022), pp. 3-22
Closed Access | Times Cited: 12
Robust Conformal Prediction for STL Runtime Verification under Distribution Shift
Yiqi Zhao, Bardh Hoxha, Georgios Fainekos, et al.
(2024), pp. 169-179
Open Access | Times Cited: 2
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety-Critical Systems
Saddek Bensalem, Chih-Hong Cheng, Wei Huang, et al.
Lecture notes in computer science (2023), pp. 55-76
Closed Access | Times Cited: 6
Customizable Reference Runtime Monitoring of Neural Networks Using Resolution Boxes
Changshun Wu, Ylìès Falcone, Saddek Bensalem
Lecture notes in computer science (2023), pp. 23-41
Closed Access | Times Cited: 5
Provably-Robust Runtime Monitoring of Neuron Activation Patterns
Chih-Hong Cheng
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015 (2021)
Open Access | Times Cited: 12
Unifying Evaluation of Machine Learning Safety Monitors
Joris Guérin, Raúl Ferreira, Kévin Delmas, et al.
(2022), pp. 414-422
Open Access | Times Cited: 8
Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural Networks
Vahid Hashemi, Jan Křetínský, Sabine Rieder, et al.
Lecture notes in computer science (2023), pp. 622-634
Closed Access | Times Cited: 4
Online Identification of Operational Design Domains of Automated Driving System Features*
Aniket Salvi, Gereon Weiß, Mario Trapp
2022 IEEE Intelligent Vehicles Symposium (IV) (2024), pp. 1743-1749
Closed Access | Times Cited: 1
Verifying the Generalization of Deep Learning to Out-of-Distribution Domains
Guy Amir, Osher Maayan, Tom Zelazny, et al.
Journal of Automated Reasoning (2024) Vol. 68, Iss. 3
Open Access | Times Cited: 1
RobDT: AI-enhanced Digital Twin for Space Exploration Robotic Assets
Marco Bozzano, Riccardo Bussola, M. Cristoforetti, et al.
Studies in computational intelligence (2023), pp. 183-198
Closed Access | Times Cited: 2
Into the unknown: active monitoring of neural networks (extended version)
Konstantin Kueffner, Anna Lukina, Christian Schilling, et al.
International Journal on Software Tools for Technology Transfer (2023) Vol. 25, Iss. 4, pp. 575-592
Open Access | Times Cited: 2
Correct-by-Construction Runtime Enforcement in AI – A Survey
Bettina Könighofer, Roderick Bloem, Rüdiger Ehlers, et al.
Lecture notes in computer science (2022), pp. 650-663
Closed Access | Times Cited: 4
SpecRepair: Counter-Example Guided Safety Repair of Deep Neural Networks
Fabian Bauer-Marquart, David Boetius, Stefan Leue, et al.
Lecture notes in computer science (2022), pp. 79-96
Open Access | Times Cited: 3
Box-Based Monitor Approach for Out-of-Distribution Detection in YOLO: An Exploratory Study
Weicheng He, Changshun Wu, Saddek Bensalem
Lecture notes in computer science (2024), pp. 229-239
Closed Access
Gaussian-Based and Outside-the-Box Runtime Monitoring Join Forces
Vahid Hashemi, Jan Křetínský, Sabine Rieder, et al.
Lecture notes in computer science (2024), pp. 218-228
Closed Access
Runtime Verification and AI: Addressing Pragmatic Regulatory Challenges
Christian Colombo, Gordon J. Pace, Dylan Seychell
Lecture notes in computer science (2024), pp. 225-241
Closed Access
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features
Nicolas Berthier, Amany Alshareef, James J. Sharp, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 3
Provably-Robust Runtime Monitoring of Neuron Activation Patterns
Chih-Hong Cheng
arXiv (Cornell University) (2020)
Open Access | Times Cited: 2
Runtime Verification
Lu Feng, Dana Fisman
Lecture notes in computer science (2021)
Closed Access | Times Cited: 1
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