A Appendix

A.1 Compute Usage The seven billion parameter language model we used as part of Frozen used model parallelism with To generate a 2-way question with n inner-shots, the following process is followed: 1. Sample two classes c "this is a dax" or "this is a blicket" accordingly 5. Select one of c Assign the truncated caption "this is a" to In 1. five distinct classes are sampled All images are stored at 224 224 resolution. To generate Real-Name miniImagenet, the same process is followed, except that in steps 4. and 6., "this is a dax"), the (first) class "this is a fruit bat"). For the evaluations in this paper, we again only take images from the validation set. In this work, we only consider 2-way Fast-VQA. To generate Guided-VQA, the same process is followed, except that in step 3. the (first) class name The Open-Ended miniImageNet, Real-Name miniImageneNet, Fast-VQA and Guided-VQA evaluations are available at https://fh295.github.io/frozen.html.