{"total":60,"rows":[{"id":"2410.10807","title":"HardNet: Hard-Constrained Neural Networks with Universal Approximation Guarantees","created":"2024-10-14","cited_by_count":31,"area":null},{"id":"2308.00143","title":"Formally Explaining Neural Networks within Reactive Systems","created":"2023-07-31","cited_by_count":24,"area":null},{"id":"2206.07912","title":"Double Sampling Randomized Smoothing","created":"2022-06-16","cited_by_count":22,"area":null},{"id":"2110.04363","title":"Certifying Robustness to Programmable Data Bias in Decision Trees","created":"2021-10-08","cited_by_count":21,"area":null},{"id":"2203.00938","title":"Neuro-Symbolic Verification of Deep Neural Networks","created":"2022-03-02","cited_by_count":21,"area":null},{"id":"2203.01212","title":"A Quantitative Geometric Approach to Neural-Network Smoothness","created":"2022-03-02","cited_by_count":16,"area":null},{"id":"2403.10144","title":"NLP Verification: Towards a General Methodology for Certifying Robustness","created":"2024-03-15","cited_by_count":16,"area":null},{"id":"2304.01874","title":"Incremental Verification of Neural Networks","created":"2023-04-04","cited_by_count":14,"area":null},{"id":"2408.09966","title":"Mask in the Mirror: Implicit Sparsification","created":"2024-08-19","cited_by_count":14,"area":null},{"id":"2206.11215","title":"Certifiable 3D Object Pose Estimation: Foundations, Learning Models, and Self-Training","created":"2022-06-22","cited_by_count":12,"area":null},{"id":"2501.05867","title":"Neural Network Verification is a Programming Language Challenge","created":"2025-01-10","cited_by_count":12,"area":null},{"id":"2302.05745","title":"Verifying Generalization in Deep Learning","created":"2023-02-11","cited_by_count":11,"area":null},{"id":"2404.12762","title":"How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law","created":"2024-04-19","cited_by_count":11,"area":null},{"id":"2203.11629","title":"On Neural Network Equivalence Checking using SMT Solvers","created":"2022-03-22","cited_by_count":10,"area":null},{"id":"2203.07671","title":"Safe Neurosymbolic Learning with Differentiable Symbolic Execution","created":"2022-03-15","cited_by_count":9,"area":null},{"id":"2412.08897","title":"Neural Interactive Proofs","created":"2024-12-12","cited_by_count":7,"area":null},{"id":"2212.08578","title":"Provable Fairness for Neural Network Models using Formal Verification","created":"2022-12-16","cited_by_count":6,"area":null},{"id":"2306.04026","title":"Value Functions are Control Barrier Functions: Verification of Safe Policies using Control Theory","created":"2023-06-06","cited_by_count":6,"area":null},{"id":"2309.11196","title":"When to Trust AI: Advances and Challenges for Certification of Neural Networks","created":"2023-09-20","cited_by_count":6,"area":null},{"id":"2506.01054","title":"No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks","created":"2025-06-01","cited_by_count":6,"area":null},{"id":"2412.11840","title":"Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges","created":"2024-12-16","cited_by_count":5,"area":null},{"id":"2501.15693","title":"Beyond Benchmarks: On The False Promise of AI Regulation","created":"2025-01-26","cited_by_count":4,"area":null},{"id":"2512.00164","title":"Faster Verified Explanations for Neural Networks","created":"2025-11-28","cited_by_count":4,"area":null},{"id":"2208.14403","title":"Verifiable Obstacle Detection","created":"2022-08-30","cited_by_count":3,"area":null},{"id":"2302.06086","title":"Reliability Assurance for Deep Neural Network Architectures Against Numerical Defects","created":"2023-02-13","cited_by_count":3,"area":null},{"id":"2305.18558","title":"DelBugV: Delta-Debugging Neural Network Verifiers","created":"2023-05-29","cited_by_count":3,"area":null},{"id":"2309.04819","title":"Detecting Violations of Differential Privacy for Quantum Algorithms","created":"2023-09-09","cited_by_count":3,"area":null},{"id":"2207.04231","title":"CEG4N: Counter-Example Guided Neural Network Quantization Refinement","created":"2022-07-09","cited_by_count":2,"area":null},{"id":"2312.08287","title":"On the verification of Embeddings using Hybrid Markov Logic","created":"2023-12-13","cited_by_count":2,"area":null},{"id":"2406.02024","title":"Verifying the Generalization of Deep Learning to Out-of-Distribution Domains","created":"2024-06-04","cited_by_count":2,"area":null},{"id":"2407.16800","title":"Wasserstein Distributionally Robust Shallow Convex Neural Networks","created":"2024-07-23","cited_by_count":2,"area":null},{"id":"2408.10362","title":"Query languages for neural networks","created":"2024-08-19","cited_by_count":2,"area":null},{"id":"2410.10554","title":"ROSAR: An Adversarial Re-Training Framework for Robust Side-Scan Sonar Object Detection","created":"2024-10-14","cited_by_count":2,"area":null},{"id":"2412.02029","title":"Learning Ensembles of Vision-based Safety Control Filters","created":"2024-12-02","cited_by_count":2,"area":null},{"id":"2502.14745","title":"SQL4NN: Validation and expressive querying of models as data","created":"2025-02-20","cited_by_count":2,"area":null},{"id":"2601.03201","title":"Recursive querying of neural networks via weighted structures","created":"2026-01-06","cited_by_count":2,"area":null},{"id":"2209.01710","title":"Perception Simplex: Verifiable Collision Avoidance in Autonomous Vehicles Amidst Obstacle Detection Faults","created":"2022-09-04","cited_by_count":1,"area":null},{"id":"2401.14628","title":"Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment","created":"2024-01-26","cited_by_count":1,"area":null},{"id":"2401.17062","title":"Outline of an Independent Systematic Blackbox Test for ML-based Systems","created":"2024-01-30","cited_by_count":1,"area":null},{"id":"2406.02773","title":"Cyclic Sparse Training: Is it Enough?","created":"2024-06-04","cited_by_count":1,"area":null},{"id":"2406.14265","title":"VeriFlow: Modeling Distributions for Neural Network Verification","created":"2024-06-20","cited_by_count":1,"area":null},{"id":"2505.00466","title":"A General Framework for Property-Driven Machine Learning","created":"2025-05-01","cited_by_count":1,"area":null},{"id":"2601.16510","title":"Learning to Optimize by Differentiable Programming","created":"2026-01-23","cited_by_count":1,"area":null},{"id":"2603.14818","title":"SimCert: Probabilistic Certification for Behavioral Similarity in Deep Neural Network Compression","created":"2026-03-16","cited_by_count":1,"area":null},{"id":"2604.15632","title":"Algebraic Invariants of Lightning Self-Attention","created":"2026-04-17","cited_by_count":1,"area":null},{"id":"2304.14888","title":"The Power of Typed Affine Decision Structures: A Case Study","created":"2023-04-28","cited_by_count":0,"area":null},{"id":"2310.02727","title":"Functional trustworthiness of AI systems by statistically valid testing","created":"2023-10-04","cited_by_count":0,"area":null},{"id":"2403.13441","title":"Robustness Verifcation in Neural Networks","created":"2024-03-20","cited_by_count":0,"area":null},{"id":"2405.08645","title":"Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation","created":"2024-05-14","cited_by_count":0,"area":null},{"id":"2408.10900","title":"Towards Efficient Formal Verification of Spiking Neural Network","created":"2024-08-20","cited_by_count":0,"area":null},{"id":"2504.21155","title":"Evaluation and Verification of Physics-Informed Neural Models of the Grad-Shafranov Equation","created":"2025-04-29","cited_by_count":0,"area":null},{"id":"2506.04268","title":"MUC-G4: Minimal Unsat Core-Guided Incremental Verification for Deep Neural Network Compression","created":"2025-06-03","cited_by_count":0,"area":null},{"id":"2602.06737","title":"Optimized Piecewise Affine Abstractions of Neural Networks with Learnable Activation Functions","created":"2026-02-06","cited_by_count":0,"area":null},{"id":"2605.13845","title":"Quantitative Linear Logic for Neuro-Symbolic Learning and Verification","created":"2026-05-13","cited_by_count":0,"area":null},{"id":"2606.03946","title":"MLSkip: Data Skipping for ML Filters via Lightweight Metadata","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2606.23760","title":"Engineering Reliable Autonomous Systems: Challenges and Solutions","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2607.03634","title":"The Role of Rigor in Artificial Intelligence","created":"2026-05-19","cited_by_count":0,"area":null},{"id":"2607.09489","title":"Ceci n'est pas une pipe: AI systems as semantic abstractions","created":"2026-07-10","cited_by_count":0,"area":null},{"id":"2608.19351","title":"Uncovering the Limits of Proof Sharing for Neural Networks","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2609.24397","title":"Probabilistic Modelling of Operational Design Domains, A New Approach for Testing AI Systems","created":"2026-09-21","cited_by_count":0,"area":null}],"next_cursor":null}