no code implementations • 8 Mar 2024 • Alycia N. Carey, Karuna Bhaila, Kennedy Edemacu, Xintao Wu
In-context learning (ICL) enables large language models (LLMs) to adapt to new tasks by conditioning on demonstrations of question-answer pairs and it has been shown to have comparable performance to costly model retraining and fine-tuning.
1 code implementation • 15 Sep 2023 • Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu
We focus on a decentralized notion of Differential Privacy, namely Local Differential Privacy, and apply randomization mechanisms to perturb both feature and label data at the node level before the data is collected by a central server for model training.