Before revision: Neural models often exploit superficial ("weak") features to achieve good performance, rather than deriving the more general ("strong") featuresthat we'd prefer a model to use .
After revision: Neural models often exploit superficial ("weak") features to achieve good performance, rather than deriving more general features .