Is AmI (Attacks Meet Interpretability) Robust to Adversarial Examples?
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Abstract (arXiv)
No.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Feb 2019.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 0; 2025: 1; 2026: 1.
7 papers.
- 2021A Comprehensive Evaluation Framework for Deep Model Robustnesscited by 42
- 2022Improving Robustness by Enhancing Weak Subnetscited by 13
- 2022Efficient Adversarial Training With Data Pruningcited by 7
- 2023Revisiting adversarial training for the worst-performing classcited by 4
- 2022Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Trainingcited by 1
- 2025Enhancing Adversarial Example Detection Through Model Explanationcited by 0
- 2026Adversarially Robust PAC Learning with Optimal VC Ratescited by 0
- 2026Adversarially Robust PAC Learning with Optimal VC Rates21 Sep 2026
- 2025Enhancing Adversarial Example Detection Through Model Explanation12 Mar 2025
- 2023Revisiting adversarial training for the worst-performing class17 Feb 2023
- 2022Efficient Adversarial Training With Data Pruning1 Jul 2022
- 2022Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Training14 Jun 2022
- 2022Improving Robustness by Enhancing Weak Subnets30 Jan 2022
- 2021A Comprehensive Evaluation Framework for Deep Model Robustness24 Jan 2021