Top 7 Differential Privacy Papers for Language Modeling

Differential privacy is a hot topic given the many conflicting opinions on its effectiveness. For some background, we previously wrote a comprehensive post on the Basics of Differential Privacy where we discussed the risks and how it can also enhance natural language understanding (NLU) models.  The differential privacy papers in this post are just a … Read more

Rappel

Testé sur un ensemble de données composé de données conversationnelles désordonnées contenant des informations de santé sensibles. Téléchargez notre livre blanc pour plus de détails, ainsi que nos performances en termes d’exactitude et de score F1, ou contactez-nous pour obtenir une copie du code d’évaluation.

99.5%+ Accuracy

Number quoted is the number of PII words missed as a fraction of total number of words. Computed on a 268 thousand word internal test dataset, comprising data from over 50 different sources, including web scrapes, emails and ASR transcripts.

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