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  1. ; ; ( , IEEE)
    Free, publicly-accessible full text available June 24, 2025
  2. ; ; ; ; ( , ACM)
    Free, publicly-accessible full text available April 14, 2025
  3. ; ; ( , AISoLA 2023)
    Free, publicly-accessible full text available December 1, 2024
  4. ; ; ( , Formal Methods for Industrial Critical Systems. FMICS 2023)
    Accepted Manuscript Full Text Available
  5. ; ; ( , Proceedings of the International Conference on Embedded Software (EMSOFT '23))
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  6. ; ; ; ( , Computer Aided Verification)
    Accepted Manuscript Full Text Available
  7. ; ; ; ; ( , International Journal on Software Tools for Technology Transfer)
    This paper presents a summary and meta-analysis of the first three iterations of the annual International Verification of Neural Networks Competition (VNN-COMP), held in 2020, 2021, and 2022. In the VNN-COMP, participants submit software tools that analyze whether given neural networks satisfy specifications describing their input-output behavior. These neural networks and specifications cover a variety of problem classes and tasks, corresponding to safety and robustness properties in image classification, neural control, reinforcement learning, and autonomous systems. We summarize the key processes, rules, and results, present trends observed over the last three years, and provide an outlook into possible future developments. 
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