I was browsing the repository, and I found this page with potential checks that can be applied to better evaluate attacks (https://github.com/fra31/auto-attack/blob/master/flags_doc.md)
We worked on a similar topic, and we published a preprint in June (https://arxiv.org/abs/2106.09947) where we develop indicators that trigger when an evaluation is faulty (and among these indicators, there is also the zero-gradient check). In the process, we also evaluated AutoPGD, showing that our systematic checks can patch failures that the automatic algorithm is unable to find.
We also released the code of our research on GitHub (https://github.com/pralab/IndicatorsOfAttackFailure).
It would be great if you could add a reference to our paper/code to that page, as the underlying idea is essentially very similar. Hence, interested users can benefit from both sources as well.
Good evening!
I was browsing the repository, and I found this page with potential checks that can be applied to better evaluate attacks (https://github.com/fra31/auto-attack/blob/master/flags_doc.md) We worked on a similar topic, and we published a preprint in June (https://arxiv.org/abs/2106.09947) where we develop indicators that trigger when an evaluation is faulty (and among these indicators, there is also the zero-gradient check). In the process, we also evaluated AutoPGD, showing that our systematic checks can patch failures that the automatic algorithm is unable to find. We also released the code of our research on GitHub (https://github.com/pralab/IndicatorsOfAttackFailure).
It would be great if you could add a reference to our paper/code to that page, as the underlying idea is essentially very similar. Hence, interested users can benefit from both sources as well.
Thank you in advance!