From: ICML.cc/2021/Workshop/AML/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: This paper proposes MAT for training robust models against patch attacks. The effectiveness is verified on different datasets.

From: ICML.cc/2021/Workshop/AML/Paper9/Reviewer_upAi
title: Interesting work
review: This paper proposes the meta adversarial training (MAT) method, which meta learns an initialization and uses I-FGSM to craft adversarial patches during training. This strategy is more efficient compared to previous methods and is empirically verified on different datasets. MAT can effectively defend against physical attacks and is worthy of more attention from the community.
rating: Accept
confidence: 5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature