Before revision: Most adversarial attack methods on text classification are designed to change the classifier's prediction by modifying few words or characters. Few try to attack classifiers by rewriting a whole sentence, due to the difficulties inherent in sentence-level rephrasing and the problem of maintaining high semantic similarity and sentence quality. To tackle this problem, we design a general sentence rewriting sampler ( SRS)framework, which can conditionally generate meaningful sentences.
After revision: Most adversarial attack methods on text classification are designed to change the classifier's prediction by synonym substitution. We propose the adversarial sentence rewriting sampler ( SRS)framework, which can conditionally generate meaningful sentences.