Adversarial editing is a common technique used for attribute transfer. In the reviewed paper, the authors applied the technique on entangled latent representations to build a controllable and flexible model for text attribute transfer. In our ablation study, we studied the effect of latent space dimension and number of Transformer layers on the performance of the original model. We found that the pre-trained model provided by the authors had a lower performance than the reported performance. In addition, we have reported several issues regarding the model implementation, but we believe that the overall structure of the model design remains correct and valid.