9 citations · 9 across the 1 of their papers we have counts for
2 papers
cs.CR2024
CoreGuard: Safeguarding Foundational Capabilities of LLMs Against Model Stealing in Edge Deployment
Qinfeng Li, Tianyue Luo, Xuhong Zhang +8
Proprietary large language models (LLMs) exhibit strong generalization capabilities across diverse tasks and are increasingly deployed on edge devices for efficiency and privacy re…
cs.LG2023★ 9 cited
SigOpt Mulch: An Intelligent System for AutoML of Gradient Boosted Trees
Aleksei Sorokin, Xinran Zhu, Eric Hans Lee +1
Gradient boosted trees (GBTs) are ubiquitous models used by researchers, machine learning (ML) practitioners, and data scientists because of their robust performance, interpretable…