1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2025
Private LoRA Fine-tuning of Open-Source LLMs with Homomorphic Encryption
Jordan Frery, Roman Bredehoft, Jakub Klemsa +2
Preserving data confidentiality during the fine-tuning of open-source Large Language Models (LLMs) is crucial for sensitive applications. This work introduces an interactive protoc…
cs.CR2024★ 1 cited
Neural Network Training on Encrypted Data with TFHE
Luis Montero, Jordan Frery, Celia Kherfallah +2
We present an approach to outsourcing of training neural networks while preserving data confidentiality from malicious parties. We use fully homomorphic encryption to build a unifi…
cs.LG2023
The Inhibitor: ReLU and Addition-Based Attention for Efficient Transformers under Fully Homomorphic Encryption on the Torus
Rickard Brännvall, Andrei Stoian
To enhance the computational efficiency of quantized Transformers, we replace the dot-product and Softmax-based attention with an alternative mechanism involving addition and ReLU…