mlsanityData to 7 Oct 2026

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks

arXiv 2401.14461 ↗First posted 25 Jan 2024cs.AI cs.LG cs.LOcited by 81

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Abstract (arXiv)

This paper serves as a comprehensive system description of version 2.0 of the Marabou framework for formal analysis of neural networks. We discuss the tool's architectural design and highlight the major features and components introduced since its initial release.

Key facts. Cited by 81 papers in the map (data through 7 Oct 2026). Builds on 48 of its 77 references that are in the map. First posted on arXiv 25 Jan 2024.

Builds on

48 of 77 references.

References · 48

  1. 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
  2. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,040
  3. 2021Convex optimizationcited by 2,479
  4. 2015Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Codingcited by 2,291
  5. 2017Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inferencecited by 1,548
  6. 2016SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model sizecited by 1,054
  7. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  8. 2017Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networkscited by 739
  9. 2018Efficient Neural Network Robustness Certification with General Activation Functionscited by 439
  10. 2015Understanding Neural Networks Through Deep Visualizationcited by 332
  11. 2018On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Modelscited by 322
  12. 2021Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verificationcited by 224
36 more
  1. 2018Efficient Formal Safety Analysis of Neural Networkscited by 165
  2. 2018Abduction-Based Explanations for Machine Learning Modelscited by 159
  3. 2020NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systemscited by 128
  4. 2022General Cutting Planes for Bound-Propagation-Based Neural Network Verificationcited by 102
  5. 2022Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Boundcited by 92
  6. 2021PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximationscited by 77
  7. 2018Deep Neural Network Compression for Aircraft Collision Avoidance Systemscited by 58
  8. 2021On Guaranteed Optimal Robust Explanations for NLP Modelscited by 54
  9. 2022Towards Formal XAI: Formally Approximate Minimal Explanations of Neural Networkscited by 42
  10. 2023The Fourth International Verification of Neural Networks Competition (VNN-COMP 2023): Summary and Resultscited by 38
  11. 2020Parallelization Techniques for Verifying Neural Networkscited by 36
  12. 2021Towards Scalable Verification of Deep Reinforcement Learningcited by 33
  13. 2022Verifying Learning-Based Robotic Navigation Systemscited by 33
  14. 2022VeriX: Towards Verified Explainability of Deep Neural Networkscited by 30
  15. 2021Verification of Image-based Neural Network Controllers Using Generative Modelscited by 27
  16. 2020Global Optimization of Objective Functions Represented by ReLU Networkscited by 24
  17. 2022Efficient Neural Network Analysis with Sum-of-Infeasibilitiescited by 24
  18. 2023Formally Explaining Neural Networks within Reactive Systemscited by 24
  19. 2022Neural Network Verification with Proof Productioncited by 22
  20. 2022Neuro-Symbolic Verification of Deep Neural Networkscited by 21
  21. 2021Pruning and Slicing Neural Networks using Formal Verificationcited by 20
  22. 2020Robustness Certification of Generative Modelscited by 19
  23. 2022Scalable Verification of GNN-based Job Schedulerscited by 18
  24. 2023Closed-loop Analysis of Vision-based Autonomous Systems: A Case Studycited by 18
  25. 2022Toward Certified Robustness Against Real-World Distribution Shiftscited by 16
  26. 2021Minimal Multi-Layer Modifications of Deep Neural Networkscited by 14
  27. 2023From Robustness to Explainability and Back Againcited by 14
  28. 2024Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programscited by 14
  29. 2022Towards Reliable Neural Specificationscited by 12
  30. 2021DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifierscited by 11
  31. 2023Towards Efficient Verification of Quantized Neural Networkscited by 10
  32. 2020Learning Event-triggered Control from Data through Joint Optimizationcited by 9
  33. 2020Verification of Neural Networks: Enhancing Scalability through Pruningcited by 8
  34. 2021SpecRepair: Counter-Example Guided Safety Repair of Deep Neural Networkscited by 6
  35. 2023Towards a Certified Proof Checker for Deep Neural Network Verificationcited by 6
  36. 2022VPN: Verification of Poisoning in Neural Networkscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 18; 2025: 30; 2026: 33.

81 papers.

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  1. 2024Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planescited by 33
  2. 2024Local vs. Global Interpretability: A Computational Complexity Perspectivecited by 23
  3. 2024Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificatescited by 15
  4. 2024Verification-Guided Shielding for Deep Reinforcement Learningcited by 13
  5. 2025Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanationscited by 13
  6. 2024Shield Synthesis for LTL Modulo Theoriescited by 12
  7. 2025Neural Network Verification is a Programming Language Challengecited by 12
  8. 2024Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretationcited by 11
  9. 2025Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasonscited by 11
  10. 2026Formal Mechanistic Interpretability: Automated Circuit Discovery with Provable Guaranteescited by 10
  11. 2025Clip-and-Verify: Linear Constraint-Driven Domain Clipping for Accelerating Neural Network Verificationcited by 9
  12. 2025SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelismcited by 8
38 more
  1. 2024Analyzing Adversarial Inputs in Deep Reinforcement Learningcited by 7
  2. 2024A Certified Proof Checker for Deep Neural Network Verification in Imandracited by 7
  3. 2024Set-Based Training for Neural Network Verificationcited by 6
  4. 2025Out of the Shadows: Exploring a Latent Space for Neural Network Verificationcited by 6
  5. 2024SoundnessBench: A Soundness Benchmark for Neural Network Verifierscited by 5
  6. 2025Abstraction-Based Proof Production in Formal Verification of Neural Networkscited by 5
  7. 2024Towards Formal Verification of Deep Neural Networks for Object Detectioncited by 4
  8. 2024Safe and Reliable Training of Learning-Based Aerospace Controllerscited by 4
  9. 2024Certifying Robustness of Learning-Based Keypoint Detection and Pose Estimation Methodscited by 4
  10. 2024Efficiently Computing Compact Formal Explanationscited by 4
  11. 2024Revisiting Differential Verification: Equivalence Verification with Confidencecited by 4
  12. 2025Logic Gate Neural Networks are Good for Verificationcited by 4
  13. 2025Proof Minimization in Neural Network Verificationcited by 4
  14. 2025PICID: Proof-Driven Clause Learning in Neural Network Verificationcited by 3
  15. 2025Probabilistic Robustness Analysis in High Dimensional Space: Application to Semantic Segmentation Networkcited by 3
  16. 2025Additive Models Explained: A Computational Complexity Approachcited by 3
  17. 2026FAME: Formal Abstract Minimal Explanation for Neural Networkscited by 3
  18. 2024Distributionally Robust Policy and Lyapunov-Certificate Learningcited by 2
  19. 2025Exact Upper and Lower Bounds for the Output Distribution of Neural Networks with Random Inputscited by 2
  20. 2025Probabilistically Tightened Linear Relaxation-based Perturbation Analysis for Neural Network Verificationcited by 2
  21. 2025Floating-Point Neural Network Verification at the Software Levelcited by 2
  22. 2026Incremental Neural Network Verification via Learned Conflictscited by 2
  23. 2024VeriFlow: Modeling Distributions for Neural Network Verificationcited by 1
  24. 2025Proof-Carrying Neuro-Symbolic Codecited by 1
  25. 2025A General Framework for Property-Driven Machine Learningcited by 1
  26. 2025Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verificationcited by 1
  27. 2025Mini-Batch Robustness Verification of Deep Neural Networkscited by 1
  28. 2025Bridging Efficiency and Safety: Formal Verification of Neural Networks with Early Exitscited by 1
  29. 2026SETA: Statistical Fault Attribution for Compound AI Systemscited by 1
  30. 2026Provably Explaining Neural Additive Modelscited by 1
  31. 2026Unifying Formal Explanations: A Complexity-Theoretic Perspectivecited by 1
  32. 2026IoUCert: Robustness Verification for Anchor-based Object Detectorscited by 1
  33. 2026VNN-LIB 2.0: Rigorous Foundations for Neural Network Verificationcited by 1
  34. 2026Lookahead Branching for Neural Network Verificationcited by 1
  35. 2026ZonoGPT: Towards An Abstract Domain for Verifying Large GPT Modelscited by 1
  36. 2024Probabilistic ML Verification via Weighted Model Integrationcited by 0
  37. 2025BoxRL-NNV: Boxed Refinement of Latin Hypercube Samples for Neural Network Verificationcited by 0
  38. 2025VeRecycle: Reclaiming Guarantees from Probabilistic Certificates for Stochastic Dynamical Systems after Changecited by 0

50 most cited of 81 All 81 (JSON)