This report summarizes the 3rd International Verification of Neural Networks
Competition (VNN-COMP 2022), held as a part of the 5th Workshop on Formal
Methods for ML-Enabled Autonomous Systems (FoMLAS), which was collocated with
the 34th 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 2022 iteration, 11 teams participated on a diverse set of
12 scored benchmarks. This report summarizes the rules, benchmarks,
participating tools, results, and lessons learned from this iteration of this
competition.

这篇文章总结了第三届国际神经网络验证竞赛（VNN-COMP 2022），它是第 5 届面向机器学习自主系统的形式方法研讨会（FoMLAS）的一部分，旨在促进当前最先进的神经网络验证工具的公平客观比较，鼓励工具接口的标准化，并聚集神经网络验证社区。在 2022 年的竞赛中，有 11 支团队参加了 12 个测评基准测试。