Papers › Adversarial Training for Free!
Adversarial Training for Free!
Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein
Adversarial training, in which a network is trained on adversarial examples, is one of the few defenses against adversarial attacks that withstands strong attacks. Unfortunately, the high cost of generating strong adversarial examples makes standard adversarial training impractical on large-scale problems like ImageNet. We present an algorithm that eliminates the overhead cost of generating adversarial examples by recycling the gradient information computed when updating model parameters. Our "free" adversarial training algorithm achieves comparable robustness to PGD adversarial training on the CIFAR-10 and CIFAR-100 datasets at negligible additional cost compared to natural training, and can be 7 to 30 times faster than other strong adversarial training methods. Using a single workstation with 4 P100 GPUs and 2 days of runtime, we can train a robust model for the large-scale ImageNet classification task that maintains 40% accuracy against PGD attacks. The code is available at https://github.com/ashafahi/free_adv_train.
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Code
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7125f3a9f5bb8e47 · report
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Adversarial Defense | ImageNet (non-targeted PGD, max perturbation=4) | ResNet-152 free-m=4 | Accuracy | 36.0% | #3 of 5 | Archive leaderboard | report |
| Adversarial Defense | ImageNet (non-targeted PGD, max perturbation=4) | ResNet-101 free-m=4 | Accuracy | 34.3% | #4 of 5 | Archive leaderboard | report |
| Adversarial Defense | ImageNet (non-targeted PGD, max perturbation=4) | ResNet-50 free-m=4 | Accuracy | 31.8% | #5 of 5 | Archive leaderboard | report |
| Domain Generalization | VizWiz-Classification | ResNet-50 (adv-train-free) | Accuracy - All Images | 26.7 | #85 of 90 | Archive leaderboard | report |
| Domain Generalization | VizWiz-Classification | ResNet-50 (adv-train-free) | Accuracy - Clean Images | 30.9 | #85 of 90 | Archive leaderboard | report |
| Domain Generalization | VizWiz-Classification | ResNet-50 (adv-train-free) | Accuracy - Corrupted Images | 20.5 | #85 of 90 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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