Abstract: Adversarial editing is a common technique used for attribute transfer. In the reviewed pa- per, the authors applied the technique on en- tangled latent representations to build a con- trollable 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 per- formance than the reported performance. In addition, we have reported several issues re- garding the model implementation, but we be- lieve that the overall structure of the model de- sign remains correct and valid.
NeurIPS Paper Id: https://openreview.net/forum?id=SyeoerSlUB