On protecting the data privacy of large language models (llms): A survey
Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …
understanding, generating and translating human language. They learn language patterns …
Grounding foundation models through federated transfer learning: A general framework
Foundation Models (FMs) such as GPT-4 encoded with vast knowledge and powerful
emergent abilities have achieved remarkable success in various natural language …
emergent abilities have achieved remarkable success in various natural language …
East: Efficient and accurate secure transformer framework for inference
Y Ding, H Guo, Y Guan, W Liu, J Huo, Z Guan… - arXiv preprint arXiv …, 2023 - arxiv.org
Transformer has been successfully used in practical applications, such as ChatGPT, due to
its powerful advantages. However, users' input is leaked to the model provider during the …
its powerful advantages. However, users' input is leaked to the model provider during the …
Promptcrypt: Prompt encryption for secure communication with large language models
Cloud-based large language models (LLMs) such as ChatGPT have increasingly become
integral to daily operations, serving as vital tools across various applications. While these …
integral to daily operations, serving as vital tools across various applications. While these …
Split-and-Denoise: Protect large language model inference with local differential privacy
P Mai, R Yan, Z Huang, Y Yang, Y Pang - arXiv preprint arXiv:2310.09130, 2023 - arxiv.org
Large Language Models (LLMs) shows powerful capability in natural language
understanding by capturing hidden semantics in vector space. This process enriches the …
understanding by capturing hidden semantics in vector space. This process enriches the …
Converting transformers to polynomial form for secure inference over homomorphic encryption
Designing privacy-preserving deep learning models is a major challenge within the deep
learning community. Homomorphic Encryption (HE) has emerged as one of the most …
learning community. Homomorphic Encryption (HE) has emerged as one of the most …
Pencil: Private and Extensible Collaborative Learning without the Non-Colluding Assumption
The escalating focus on data privacy poses significant challenges for collaborative neural
network training, where data ownership and model training/deployment responsibilities …
network training, where data ownership and model training/deployment responsibilities …
[PDF][PDF] Towards confidential chatbot conversations: A decentralised federated learning framework
The development of cutting-edge large language models such as ChatGPT has sparked
global interest in the transformative potential of chatbots to automate language tasks …
global interest in the transformative potential of chatbots to automate language tasks …
Data-Centric AI in the Age of Large Language Models
This position paper proposes a data-centric viewpoint of AI research, focusing on large
language models (LLMs). We start by making the key observation that data is instrumental in …
language models (LLMs). We start by making the key observation that data is instrumental in …
[HTML][HTML] SecureTLM: Private inference for transformer-based large model with MPC
Y Chen, X Meng, Z Shi, Z Ning, J Lin - Information Sciences, 2024 - Elsevier
Abstract Transformer-based Large Models (TLM), such as generative pre-trained models
(GPT), have become increasingly popular for practical applications through Deep Learning …
(GPT), have become increasingly popular for practical applications through Deep Learning …