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This report summarizes the 3rd International Verification of Neural NetworksCompetition (VNN-COMP 2022), held as a part of the 5th Workshop on FormalMethods for ML-Enabled Autonomous Systems (FoMLAS), which was collocated withthe 34th International Conference on Computer-Aided Verification (CAV).VNN-COMP is held annually to facilitate the fair and objective comparison ofstate-of-the-art neural network verification tools, encourage thestandardization of tool interfaces, and bring together the neural networkverification community. To this end, standardized formats for networks (ONNX)and specification (VNN-LIB) were defined, tools were evaluated on equal-costhardware (using an automatic evaluation pipeline based on AWS instances), andtool parameters were chosen by the participants before the final test sets weremade public. In the 2022 iteration, 11 teams participated on a diverse set of12 scored benchmarks. This report summarizes the rules, benchmarks,participating tools, results, and lessons learned from this iteration of thiscompetition.

The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results