Provably Confidential Language Modelling. (arXiv:2205.01863v2 [cs.CL] UPDATED)

Large language models are shown to memorize privacy information such as
social security numbers in training data. Given the sheer scale of the training
corpus, it is challenging to screen and filter these privacy data, either
manually or automatically. In this paper, we propose Confidentially Redacted
Training (CRT), a method to train language generation models while protecting
the confidential segments. We borrow ideas from differential privacy (which
solves a related but distinct problem) and show that our method is able …

confidential language