Before revision: While there has been great interest in generating imperceptible adversarial examples in continuous data domain (e.g. image and audio)to explore the model vulnerabilities, generatingadversarial text in the discrete domain is still challenging . The main contribution of this paper is to propose a general targeted attack framework AdvCodec for adversarial text generation which addresses the challenge of discrete input space and is easily adapted to general natural language processing (NLP )  tasks.
After revision: While there has been great interest in generating imperceptible adversarial examples in continuous data domain (e.g. image and audio)to explore the model vulnerabilities, generatingadversarial text , image ) tasks.