mlsanityData to 14 Oct 2026

Neural Network Verification is a Programming Language Challenge

arXiv 2501.05867 ↗First posted 10 Jan 2025cs.PL cs.LG cs.LOcited by 12

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Abstract (arXiv)

Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while proper support from the programming language perspective has been considered secondary or unimportant. Yet, there is mounting evidence that insights from the programming language community may make a difference in the future development of this domain. In this paper, we formulate neural network verification challenges as programming language challenges and suggest possible future solutions.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 65 of its 125 references that are in the map. First posted on arXiv 10 Jan 2025.

Builds on

65 of 125 references.

References · 65

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  5. 2017Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networkscited by 744
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38 more
  1. 2020NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systemscited by 128
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  4. 2024Marabou 2.0: A Versatile Formal Analyzer of Neural Networkscited by 81
  5. 2017Output Reachable Set Estimation and Verification for Multi-Layer Neural Networkscited by 80
  6. 2017Verifying Properties of Binarized Deep Neural Networkscited by 79
  7. 2021The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Resultscited by 71
  8. 2018TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzingcited by 68
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  11. 2023First Three Years of the International Verification of Neural Networks Competition (VNN-COMP)cited by 58
  12. 2022Certified Training: Small Boxes are All You Needcited by 52
  13. 2020An SMT-Based Approach for Verifying Binarized Neural Networkscited by 47
  14. 2022Deep Learning with Logical Constraintscited by 44
  15. 2024The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Resultscited by 43
  16. 2021POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systemscited by 39
  17. 2023The Fourth International Verification of Neural Networks Competition (VNN-COMP 2023): Summary and Resultscited by 38
  18. 2020Exploiting Verified Neural Networks via Floating Point Numerical Errorcited by 35
  19. 2021Neural Network Robustness as a Verification Property: A Principled Case Studycited by 35
  20. 2020Efficient Exact Verification of Binarized Neural Networkscited by 33
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50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 7; 2026: 5.

12 papers.

  1. 2025No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networkscited by 6
  2. 2025Proof Minimization in Neural Network Verificationcited by 4
  3. 2025Floating-Point Neural Network Verification at the Software Levelcited by 2
  4. 2025Proof-Carrying Neuro-Symbolic Codecited by 1
  5. 2026VNN-LIB 2.0: Rigorous Foundations for Neural Network Verificationcited by 1
  6. 2025Neural Network Verification for Gliding Drone Control: A Case Studycited by 0
  7. 2025The CAISAR Platform: Extending the Reach of Machine Learning Specification and Verificationcited by 0
  8. 2025Of Good Demons and Bad Angels: Guaranteeing Safe Control under Finite Precisioncited by 0
  9. 2026Delayed Backdoor Attacks: Exploring the Temporal Dimension as a New Attack Surface in Pre-Trained Modelscited by 0
  10. 2026Lipschitz-Based Robustness Certification Under Floating-Point Executioncited by 0
  11. 2026DeepFix: Debugging and Fixing Machine Learning Workflow using Agentic AIcited by 0
  12. 2026Logic-Gated Time-Shared Feedforward Networks for Alternating Finite Automata: Exact Simulation and Learnabilitycited by 0