5 citations · 14 across the 9 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.CR2024★ 2 cited
LLM-PBE: Assessing Data Privacy in Large Language Models
Qinbin Li, Junyuan Hong, Chulin Xie +10
Large Language Models (LLMs) have become integral to numerous domains, significantly advancing applications in data management, mining, and analysis. Their profound capabilities in…
cs.LG2024★ 1 cited
Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk
Zhangheng Li, Junyuan Hong, Bo Li +1
While diffusion models have recently demonstrated remarkable progress in generating realistic images, privacy risks also arise: published models or APIs could generate training ima…
cs.CL2024★ 4 cited
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang +12
Compressing high-capability Large Language Models (LLMs) has emerged as a favored strategy for resource-efficient inferences. While state-of-the-art (SoTA) compression methods boas…