“…Most are discussed in Emmery et al (2021); however, some new work is specifically of interest to data augmentation, such as improving the substitutions using beam search (Zhao et al, 2021, as opposed to the simultaneous rollout we used in the current work). More broadly, adversarial training (Si et al, 2021;Pan et al, 2021), implementing more robust stylometric features (Markov et al, 2021), or modelbased weightings of the augmentation models could be explored; e.g., by selecting instances with a generation model in the loop (Anaby-Tavor et al, 2020). This could be a particularly worthwhile option when focusing on conversation scopes, rather than message-level cyberbullying content (Emmery et al, 2019).…”