Seonglae ChoAI Data Security Notion
Privacy Considerations in Large Language Models
Machine learning-based language models trained to predict the next word in a sentence have become increasingly capable, common, and useful, leading to groundbreaking improvements in applications like question-answering, translation, and more. But as language models continue to advance, new and unexpected risks can be exposed, requiring the research community to proactively work to develop new ways to mitigate potential problems.
https://blog.research.google/2020/12/privacy-considerations-in-large.html
Data extraction
Scalable Extraction of Training Data from (Production) Language Models
This paper studies extractable memorization: training data that an adversary can efficiently extract by querying a machine learning model without prior knowledge of the training dataset. We show...
https://arxiv.org/abs/2311.17035
