LearningtoReasonIterativelyandParallellyfor ComplexVisualReasoningScenarios

Meanwhile, its"parallel" computation allowsforthesimultaneous explorationofdifferent reasoning paths andbenefits more robust and efficient execution of operations that are mutually independent (e.g. when counting individual colors for the query:"determine the maximum occurring color amongst all t-shirts"). We design IPRM as a lightweight and fully-differentiable neural module thatcanbeconveniently applied toboth transformer and non-transformer vision-language backbones.