RobustBench / robustbench

RobustBench: a standardized adversarial robustness benchmark [NeurIPS 2021 Benchmarks and Datasets Track]
https://robustbench.github.io
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[New Model] RodriguezMunoz2024Characterizing #195

Open adriarm opened 1 month ago

adriarm commented 1 month ago

Paper Information

The focus of the paper is on efficient robust training using gradient regularisation, and showing it is surprisingly effective on ImageNet.

Leaderboard Claim(s)

Our model can be instantiated and benchmarked by:

  1. Cloning our code and following environment install instructions.
  2. Downloading our checkpoint
  3. Setting data_dir, arch and ckpt_location in benchmark_model.py
  4. Running benchmark_model.py

The models use the Swin architecture from the old timm==0.6.7 version. If it is preferred for me to write the pull request, please let me know what the best way to implement it is.

Model 1

Model 2

Model Zoo:

fra31 commented 1 month ago

Hi,

thanks for the submission! I'll try to add the models in the next days.

adriarm commented 4 days ago

Perfect, thank you so much! When do you think the models will be able to appear on the leaderboard? Please let me know if there are any issues.