Jiankun Hu

Generative Textual Adversarial Attack Through Extensible Compositional Perturbation via Reinforcement Learning for Policy Optimization

As textual adversarial attacks pose risks to natural language processing models, adversarial training is often utilized to improve robustness of these systems. In a strict black-box scenario, most query-based textual adversarial attack methods rely on fixed or limited perturbation policies and search in the perturbatio...