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Found 4 papers, 4 papers with code
A Strong Baseline for Query Efficient Attacks in a Black Box Setting
Also, prior attacks do not maintain a consistent search space while comparing different search methods.
Generating Natural Language Attacks in a Hard Label Black Box Setting
Our proposed attack strategy leverages population-based optimization algorithm to craft plausible and semantically similar adversarial examples by observing only the top label predicted by the target model.
A Context Aware Approach for Generating Natural Language Attacks
We study an important task of attacking natural language processing models in a black box setting.
AutoLearn - Automated Feature Generation and Selection
In recent years, the importance of feature engineering has been confirmed by the exceptional performance of deep learning techniques, that automate this task for some applications.
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