Venue: ICML 2021 Workshop AML

Reviews:

final_score: rating: Accept
review_content: 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.
review_title: The phenomenon is interesting. More theoretical analysis should be included.

Meta-review: This paper showed that can greatly transfer between slightly-robust networks and target networks. The finding is interesting and might have inspire future work.
Decision: Accept (Poster)