Before revision:  We then construct an augmentation of the VQA dataset  with questions containing logical operations and retrain the same models to establish a baseline. We further propose a novel methodology to train models to learn negation, conjunction, and disjunction and show }  improvement in learning logical composition and retaining performance on VQA.
After revision:  We then construct an augmentation of the VQA dataset with questions containing logical compositions and linguistic transformations (negation, disjunction, conjunction, and antonyms). We propose our } improvement in learning logical composition and retaining performance on VQA.