Large language models can be strong differentially private learners
X Li, F Tramer, P Liang, T Hashimoto - ar**: Differentially private deep learning made easier and stronger
Per-example gradient clip** is a key algorithmic step that enables practical differential
private (DP) training for deep learning models. The choice of clip** threshold $ R …
private (DP) training for deep learning models. The choice of clip** threshold $ R …
Privacy-preserving prompt tuning for large language model services
Prompt tuning provides an efficient way for users to customize Large Language Models
(LLMs) with their private data in the emerging LLM service scenario. However, the sensitive …
(LLMs) with their private data in the emerging LLM service scenario. However, the sensitive …
Federated large language model: A position paper
Large scale language models (LLM) have received significant attention and found diverse
applications across various domains, but their development encounters challenges in real …
applications across various domains, but their development encounters challenges in real …
Preserving privacy in large language models: A survey on current threats and solutions
Large Language Models (LLMs) represent a significant advancement in artificial
intelligence, finding applications across various domains. However, their reliance on …
intelligence, finding applications across various domains. However, their reliance on …