Common Clarifications: (CC1) Evaluation with other datasets (VQA-CP, GQA) @R1, R2, R4: The main focus and

We thank all the reviewers for their insightful questions, comments and commendations (novelty, clarity, performance). T ask 1 motivation, complexity @R3, R4: Motivation behind Task 1 is efficacy, not complexity [L46-49]. GVQA (from VQA-CP) builds on stacked attention networks (SAN). Thus, they are orthogonal to MGN in problem setting and architecture. We show results using MAC (from the GQA authors, L291) with both CLEVR and GQA results.