Besides, binarymask has less semantic meanings compared toinstance labels and semantic labels.

Fairness and robustness are critical elements of Trustworthy AI that need to be addressedtogether.

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.

In the field of natural language processing, the prevalent approach involves fine-tuning pretrained language models (PLMs) using local samples.