4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Privacy Evaluation Benchmarks for NLP Models
Wei Huang, Yinggui Wang, Cen Chen
By inducing privacy attacks on NLP models, attackers can obtain sensitive information such as training data and model parameters, etc. Although researchers have studied, in-depth,…
cs.CR2024
Privacy-Preserving End-to-End Spoken Language Understanding
Yinggui Wang, Wei Huang, Le Yang
Spoken language understanding (SLU), one of the key enabling technologies for human-computer interaction in IoT devices, provides an easy-to-use user interface. Human speech can co…
cs.LG2024★ 4 cited
A Fast, Performant, Secure Distributed Training Framework For Large Language Model
Wei Huang, Yinggui Wang, Anda Cheng +3
The distributed (federated) LLM is an important method for co-training the domain-specific LLM using siloed data. However, maliciously stealing model parameters and data from the s…