From: ICML.cc/2021/Workshop/AML/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: This paper showed that can greatly transfer between slightly-robust networks and target networks. The finding is interesting and might have inspire future work.

From: ICML.cc/2021/Workshop/AML/Paper57/Reviewer_sgoT
title: The phenomenon is interesting. More theoretical analysis should be included.
review: In this work, the authors show that adversarial examples can greatly transfer between slightly-robust networks and target networks. The paper show that these adversarial examples can transfer representation layer features substantially better than adversarial examples generated with non-robust networks.  The authors argue that this result supports a non-intuitive hypothesis that slightly robust networks exhibit universal features.

Pros: The uncovered phenomenon is really interesting. Experiment results are given to support the argument.

Cons: Although the phenomenon is really interesting, it is non-intuitive. More theoretical analysis should be included to demonstrate why this would happen.
rating: Accept
confidence: 4: The reviewer is confident but not absolutely certain that the evaluation is correct