Semantic Stealth: Adversarial Text Attacks on NLP Using Several Methods

arXiv:2404.05159v1 Announce Type: cross
Abstract: In various real-world applications such as machine translation, sentiment analysis, and question answering, a pivotal role is played by NLP models, facilitating efficient communication and decision-making processes in domains ranging from healthcare to finance. However, a significant challenge is posed to the robustness of these natural language processing models by text adversarial attacks. These attacks involve the deliberate manipulation of input text to mislead the predictions of the model while maintaining human interpretability. Despite the …

adversarial analysis applications arxiv attacks challenge communication cs.cl cs.cr cs.lg decision domains finance healthcare machine making nlp processes question real robustness role semantic sentiment analysis stealth text translation world