Task: Language Identification
Input (Spanish, English): I reviewed the manuscript as of December 6th.  The authors perform a systematic investigation of various retraining methods for making a classification network robust to adversarial examples. The authors achieve lower error rates using their RAD and IAEC methods perform better then previously introduced distillation methods for retraining networks to be robust to adversarial examples. This method suggests a promising direction for building a defense for adversarial examples.  Major Comments: I find the paper to not be lacking in exposition and clarity. The paper has a laundry list of related results (page 2) but no clear message. I *think* one larger point is the superior performance of their retraining techniques but it is not clear how well these techniques perform compared to other retraining techniques, nor are the details of the retraining techniques clear. The paper requires more discussion and a clear exposition about the methods the authors introduced (i.e. RAD, IAEC). What follow are some more detailed comments along this theme of improving the exposition and clarity:  - The authors should provide more details about how they constructed the auto-encoder in the IAEC method (diagram?). The same needs to be said for the RAD method. The authors point to a previous workshop submission (
Output (English): en