Papers with embedding estimator

1 papers
Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification (D19-1)

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Challenge: Existing studies on adversarial attacks on deep learning models focus on generation of adversarials and defense against adversarial attacks.
Approach: They propose a framework to identify and adjust malicious perturbations and block adversarial attacks for machine learning models.
Outcome: The proposed framework outperforms baseline methods in blocking adversarial attacks for text classification models.

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