3 papers
cs.CR2024
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.CL2024
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…
cs.LG2024
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…