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1911.09032
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Outside the Box: Abstraction-Based Monitoring of Neural Networks
European Conference on Artificial Intelligence (ECAI), 2019
20 November 2019
T. Henzinger
Anna Lukina
Christian Schilling
AAML
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Papers citing
"Outside the Box: Abstraction-Based Monitoring of Neural Networks"
38 / 38 papers shown
Runtime Safety Monitoring of Deep Neural Networks for Perception: A Survey
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Safety Monitoring of Machine Learning Perception Functions: a Survey
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Jérémie Guiochet
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338
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09 Dec 2024
Attention Masks Help Adversarial Attacks to Bypass Safety Detectors
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A Systematic Review of Edge Case Detection in Automated Driving: Methods, Challenges and Future Directions
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Vahid Hashemi
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278
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11 Oct 2024
Gaussian-Based and Outside-the-Box Runtime Monitoring Join Forces
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Sabine Rieder
Torsten Schön
Jan Vorhoff
197
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08 Oct 2024
Monitizer: Automating Design and Evaluation of Neural Network Monitors
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Muqsit Azeem
Marta Grobelna
Sudeep Kanav
Jan Křetínský
Stefanie Mohr
Sabine Rieder
223
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0
16 May 2024
Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring
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Khoi Tran Dang
Kevin Delmas
Jérémie Guiochet
Joris Guérin
338
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14 May 2024
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward
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12 Apr 2024
BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection
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Weicheng He
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Saddek Bensalem
215
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Nikola S. Nikolov
188
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21 Mar 2024
A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks
International Conference on Computer Safety, Reliability, and Security (SAFECOMP), 2023
Florian Geissler
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Michael Paulitsch
Karthik Pattabiraman
210
7
0
31 Oct 2023
LUNA: A Model-Based Universal Analysis Framework for Large Language Models
IEEE Transactions on Software Engineering (TSE), 2023
Da Song
Xuan Xie
Yuheng Huang
Derui Zhu
Yuheng Huang
Felix Juefei Xu
Lei Ma
ALM
350
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0
22 Oct 2023
Runtime Monitoring DNN-Based Perception
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Chih-Hong Cheng
Michael Luttenberger
Rongjie Yan
190
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06 Oct 2023
SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning Agents
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Amirhossein Zolfagharian
Manel Abdellatif
Lionel C. Briand
S. Ramesh
289
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What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems
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Chih-Hong Cheng
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Changshun Wu
Xingyu Zhao
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249
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20 Jul 2023
Preventing Errors in Person Detection: A Part-Based Self-Monitoring Framework
Franziska Schwaiger
A. Matic
Karsten Roscher
Stephan Günnemann
185
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10 Jul 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
Artificial Intelligence Review (AIR), 2023
Xiaowei Huang
Wenjie Ruan
Wei Huang
Gao Jin
Yizhen Dong
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Sihao Wu
Peipei Xu
Dengyu Wu
André Freitas
Mustafa A. Mustafa
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351
143
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19 May 2023
Detection of out-of-distribution samples using binary neuron activation patterns
Computer Vision and Pattern Recognition (CVPR), 2022
Bartlomiej Olber
Krystian Radlak
A. Popowicz
Michal Szczepankiewicz
K. Chachula
OODD
224
18
0
29 Dec 2022
Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural Networks
World 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 Need
AAAI Conference on Artificial Intelligence (AAAI), 2022
Joris Guérin
Kevin Delmas
Raul Sena Ferreira
Jérémie Guiochet
OODD
296
40
0
29 Nov 2022
Correct-by-Construction Runtime Enforcement in AI -- A Survey
Bettina Könighofer
Roderick Bloem
Rüdiger Ehlers
Christian Pek
170
13
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30 Aug 2022
Prioritizing Corners in OoD Detectors via Symbolic String Manipulation
Automated 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
161
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
240
70
0
25 Sep 2021
Hack The Box: Fooling Deep Learning Abstraction-Based Monitors
Sara Al Hajj Ibrahim
M. Nassar
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160
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SpecRepair: Counter-Example Guided Safety Repair of Deep Neural Networks
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Fabian Bauer-Marquart
David Boetius
Stefan Leue
Christian Schilling
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508
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03 Jun 2021
Customizable Reference Runtime Monitoring of Neural Networks using Resolution Boxes
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Changshun Wu
Yliès Falcone
Saddek Bensalem
280
13
0
25 Apr 2021
Monitoring Object Detection Abnormalities via Data-Label and Post-Algorithm Abstractions
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Yuhang Chen
Chih-Hong Cheng
Jun Yan
Rongjie Yan
147
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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
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Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends
IEEE Access (IEEE Access), 2021
Q. Rahman
Peter Corke
Feras Dayoub
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470
64
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Provably-Robust Runtime Monitoring of Neuron Activation Patterns
Design, Automation and Test in Europe (DATE), 2020
Chih-Hong Cheng
AAML
238
13
0
24 Nov 2020
Continuous Safety Verification of Neural Networks
Chih-Hong Cheng
Rongjie Yan
236
12
0
12 Oct 2020
Into the Unknown: Active Monitoring of Neural Networks
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Anna Lukina
Christian Schilling
T. Henzinger
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398
29
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14 Sep 2020
Online Monitoring for Neural Network Based Monocular Pedestrian Pose Estimation
Arjun Gupta
Luca Carlone
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163
9
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Model Assertions for Monitoring and Improving ML Models
Conference on Machine Learning and Systems (MLSys), 2020
Daniel Kang
Deepti Raghavan
Peter Bailis
Matei A. Zaharia
284
65
0
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Input Validation for Neural Networks via Runtime Local Robustness Verification
Jiangchao Liu
Liqian Chen
A. Miné
Ji Wang
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208
11
0
09 Feb 2020
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