Furthermore, Jin et al. (2019) showed that BERT is the language model that best performs under adversary attacks when compared to CNN and LSTM in terms of success rate and perturbation rate, preservation of semantic content, and efficiency for text classification tasks.
Swap Noise: For each word in the text, one random pair of consecutive characters is swapped (e.g. expression → exrpession).