Papers citing 'Outside the Box: Abstraction-Based Monitoring of Neural Networks'

Title
Runtime Safety Monitoring of Deep Neural Networks for Perception: A Survey Albert Schotschneider Svetlana Pavlitska Johann Marius Zöllner AAML AI4CE 227 0 0 08 Nov 2025
Out-of-Distribution Detection using Counterfactual Distance Maria Stoica Francesco Leofante Alessio Lomuscio OODD 176 0 0 13 Aug 2025
Enhancing System Self-Awareness and Trust of AI: A Case Study in Trajectory Prediction and Planning Lars Ullrich Zurab Mujirishvili Knut Graichen 227 2 0 25 Apr 2025
Safety Monitoring of Machine Learning Perception Functions: a SurveyInternational Conference on Climate Informatics (ICCI), 2024 Raul Sena Ferreira Joris Guérin Kevin Delmas Jérémie Guiochet H. Waeselynck 314 4 0 09 Dec 2024
Attention Masks Help Adversarial Attacks to Bypass Safety Detectors Yunfan Shi AAML 305 0 0 07 Nov 2024
A Systematic Review of Edge Case Detection in Automated Driving: Methods, Challenges and Future Directions Saeed Rahmani Sabine Rieder Erwin de Gelder Marcel Sonntag Jorge Lorente Mallada Sytze Kalisvaart Vahid Hashemi Simeon C. Calvert 274 3 0 11 Oct 2024
Gaussian-Based and Outside-the-Box Runtime Monitoring Join ForcesRuntime Verification (RV), 2024 Vahid Hashemi Jan Křetínský Sabine Rieder Torsten Schön Jan Vorhoff 189 2 0 08 Oct 2024
Monitizer: Automating Design and Evaluation of Neural Network MonitorsInternational Conference on Computer Aided Verification (CAV), 2024 Muqsit Azeem Marta Grobelna Sudeep Kanav Jan Křetínský Stefanie Mohr Sabine Rieder 215 2 0 16 May 2024
Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network MonitoringConference on Uncertainty in Artificial Intelligence (UAI), 2024 Khoi Tran Dang Kevin Delmas Jérémie Guiochet Joris Guérin 283 1 0 14 May 2024
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward Xuan Xie Yuheng Huang Zhehua Zhou Yuheng Huang Da Song Lei Ma OffRL 385 12 0 12 Apr 2024
BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection Changshun Wu Weicheng He Chih-Hong Cheng Xiaowei Huang Saddek Bensalem 211 5 0 27 Mar 2024
On the Detection of Anomalous or Out-Of-Distribution Data in Vision Models Using Statistical Techniques Laura O'Mahony David JP O'Sullivan Nikola S. Nikolov 164 1 0 21 Mar 2024
A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural NetworksInternational Conference on Computer Safety, Reliability, and Security (SAFECOMP), 2023 Florian Geissler S. Qutub Michael Paulitsch Karthik Pattabiraman 190 7 0 31 Oct 2023
LUNA: A Model-Based Universal Analysis Framework for Large Language ModelsIEEE Transactions on Software Engineering (TSE), 2023 Da Song Xuan Xie Yuheng Huang Derui Zhu Yuheng Huang Felix Juefei Xu Lei Ma ALM 338 9 0 22 Oct 2023
Runtime Monitoring DNN-Based PerceptionRuntime Verification (RV), 2023 Chih-Hong Cheng Michael Luttenberger Rongjie Yan 182 3 0 06 Oct 2023
SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning AgentsIEEE Transactions on Software Engineering (TSE), 2023 Amirhossein Zolfagharian Manel Abdellatif Lionel C. Briand S. Ramesh 277 12 0 03 Aug 2023
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems Saddek Bensalem Chih-Hong Cheng Wei Huang Xiaowei Huang Changshun Wu Xingyu Zhao AAML 245 10 0 20 Jul 2023
Preventing Errors in Person Detection: A Part-Based Self-Monitoring Framework Franziska Schwaiger A. Matic Karsten Roscher Stephan Günnemann 181 0 0 10 Jul 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence Review (AIR), 2023 Xiaowei Huang Wenjie Ruan Wei Huang Gao Jin Yizhen Dong ... Sihao Wu Peipei Xu Dengyu Wu André Freitas Mustafa A. Mustafa ALM 347 143 0 19 May 2023
Detection of out-of-distribution samples using binary neuron activation patternsComputer Vision and Pattern Recognition (CVPR), 2022 Bartlomiej Olber Krystian Radlak A. Popowicz Michal Szczepankiewicz K. Chachula OODD 221 18 0 29 Dec 2022
Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural NetworksWorld Congress on Formal Methods (FM), 2022 V. Hashemi Jan Křetínský Sabine Rieder J. Schmidt OODD 166 9 0 15 Dec 2022
Out-Of-Distribution Detection Is Not All You NeedAAAI Conference on Artificial Intelligence (AAAI), 2022 Joris Guérin Kevin Delmas Raul Sena Ferreira Jérémie Guiochet OODD 295 39 0 29 Nov 2022
Correct-by-Construction Runtime Enforcement in AI -- A Survey Bettina Könighofer Roderick Bloem Rüdiger Ehlers Christian Pek 156 13 0 30 Aug 2022
Prioritizing Corners in OoD Detectors via Symbolic String ManipulationAutomated Technology for Verification and Analysis (ATVA), 2022 Chih-Hong Cheng Changshun Wu Emmanouil Seferis Saddek Bensalem 269 3 0 16 May 2022
Benchmarking Safety Monitors for Image Classifiers with Machine Learning Raul Sena Ferreira J. Arlat Jérémie Guiochet H. Waeselynck 160 27 0 04 Oct 2021
Beyond Robustness: A Taxonomy of Approaches towards Resilient Multi-Robot Systems Amanda Prorok Matthew Malencia Luca Carlone Gaurav Sukhatme Brian M. Sadler Vijay Kumar 235 69 0 25 Sep 2021
Hack The Box: Fooling Deep Learning Abstraction-Based Monitors Sara Al Hajj Ibrahim M. Nassar AAML 160 2 0 10 Jul 2021
SpecRepair: Counter-Example Guided Safety Repair of Deep Neural NetworksSPIN (SPIN), 2021 Fabian Bauer-Marquart David Boetius Stefan Leue Christian Schilling AAML 504 7 0 03 Jun 2021
Customizable Reference Runtime Monitoring of Neural Networks using Resolution BoxesRuntime Verification (RV), 2021 Changshun Wu Yliès Falcone Saddek Bensalem 264 13 0 25 Apr 2021
Monitoring Object Detection Abnormalities via Data-Label and Post-Algorithm AbstractionsIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2021 Yuhang Chen Chih-Hong Cheng Jun Yan Rongjie Yan 131 7 0 29 Mar 2021
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features Nicolas Berthier Amany Alshareef James Sharp S. Schewe Xiaowei Huang 165 10 0 05 Mar 2021
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging TrendsIEEE Access (IEEE Access), 2021 Q. Rahman Peter Corke Feras Dayoub OOD 441 64 0 05 Jan 2021
Provably-Robust Runtime Monitoring of Neuron Activation PatternsDesign, Automation and Test in Europe (DATE), 2020 Chih-Hong Cheng AAML 202 13 0 24 Nov 2020
Continuous Safety Verification of Neural Networks Chih-Hong Cheng Rongjie Yan 192 12 0 12 Oct 2020
Into the Unknown: Active Monitoring of Neural NetworksRuntime Verification (RV), 2020 Anna Lukina Christian Schilling T. Henzinger AAML 350 29 0 14 Sep 2020
Online Monitoring for Neural Network Based Monocular Pedestrian Pose Estimation Arjun Gupta Luca Carlone 3DH 155 9 0 11 May 2020
Model Assertions for Monitoring and Improving ML ModelsConference on Machine Learning and Systems (MLSys), 2020 Daniel Kang Deepti Raghavan Peter Bailis Matei A. Zaharia 263 65 0 03 Mar 2020
Input Validation for Neural Networks via Runtime Local Robustness Verification Jiangchao Liu Liqian Chen A. Miné Ji Wang AAML 192 11 0 09 Feb 2020