White-Box Attacks on Hate-speech BERT Classifiers in German with Explicit and Implicit Character Level Defense

英文摘要：

In this work, we evaluate the adversarial robustness of BERT models trained on German Hate Speech datasets. We also complement our evaluation with two novel white-box character and word level attacks thereby contributing to the range of attacks available. Furthermore, we also perform a comparison of two novel character-level defense strategies and evaluate their robustness with one another.