This report summarizes the 4th International Verification of Neural Networks Competition (VNN-COMP 2023), held as a part of the 6th Workshop on Formal Methods for ML-Enabled Autonomous Systems (FoMLAS), that was collocated with the 35th International Conference on Computer-Aided Verification (CAV). VNN-COMP is held annually to facilitate the fair and objective comparison of state-of-the-art neural network verification tools, encourage the standardization of tool interfaces, and bring together the neural network verification community. To this end, standardized formats for networks (ONNX) and specification (VNN-LIB) were defined, tools were evaluated on equal-cost hardware (using an automatic evaluation pipeline based on AWS instances), and tool parameters were chosen by the participants before the final test sets were made public. In the 2023 iteration, 7 teams participated on a diverse set of 10 scored and 4 unscored benchmarks. This report summarizes the rules, benchmarks, participating tools, results, and lessons learned from this iteration of this competition.

翻译：本报告总结了第四届国际神经网络验证竞赛（VNN-COMP 2023），该竞赛作为第六届机器学习赋能自主系统形式化方法研讨会（FoMLAS）的一部分举办，并与第35届国际计算机辅助验证会议（CAV）同期举行。VNN-COMP每年举办，旨在促进神经网络验证领域最新工具间的公平客观比较，鼓励工具接口标准化，并汇聚神经网络验证社区的研究力量。为此，竞赛定义了标准化的网络格式（ONNX）与规范格式（VNN-LIB），在同等计算成本的硬件上（基于AWS实例的自动评估流水线）评估工具，并要求参选者在最终测试集公开前确定工具参数。在2023届竞赛中，共有7支队伍参与了包含10个评分基准和4个非评分基准的多样化测试集。本报告总结了本届竞赛的规则、基准测试、参赛工具、结果及经验教训。