Improving Text Classification Resilience and Efficiency with RETVec

Systems such as Gmail, YouTube and Google Play rely on text classification models to identify harmful content including phishing attacks, inappropriate comments, and scams. These types of texts are harder for machine learning models to classify because bad actors rely on adversarial text manipulations to actively attempt to evade the classifiers. For example, they will use homoglyphs, invisible characters, and keyword stuffing to bypass defenses. 

To help make …