Before revision:  Crucially, our base network has the same state-of-the-art performance as prior work , 97\% execution accuracy, while at the same time generalizing its knowledge when prior work does not ; for example, achieving 95\% accuracy on novel adjective-noun compositions where previous work has 55\% average accuracy.
After revision:  Crucially, our base network has the same state-of-the-art performance as prior work , 97\% execution accuracy, while at the same time generalizing its knowledge when prior work does not . Our network also provides a level of interpretability that enables users to inspect what each part of networks learns.