DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example Generation

14 Dec 2017 Catherine Wong

Machine learning models are powerful but fallible. Generating adversarial examples - inputs deliberately crafted to cause model misclassification or other errors - can yield important insight into model assumptions and vulnerabilities... (read more)

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