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Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark

Reap Benchmark ⭐ 9

REAP: A Large-Scale Realistic Adversarial Patch Benchmark

Code and data of the EMNLP 2022 paper "Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP".

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