2 citations · 2 across the 4 of their papers we have counts for
5 papers
Fingerprinting Multimodal Large Language Models
Chao Huang, Meng Tong, Kejiang Chen
While multimodal large language models (MLLMs) enable a wide range of image-text reasoning tasks, recent incidents indicate that they are vulnerable to illicit deployment and unaut…
Membership Inference Attacks on Tokenizers of Large Language Models
Meng Tong, Yuntao Du, Kejiang Chen +2
Membership inference attacks (MIAs) are widely used to assess the privacy risks associated with machine learning models. However, when these attacks are applied to pre-trained larg…
Multimodal Prompt Decoupling Attack on the Safety Filters in Text-to-Image Models
Xingkai Peng, Jun Jiang, Meng Tong +4
Text-to-image (T2I) models have been widely applied in generating high-fidelity images across various domains. However, these models may also be abused to produce Not-Safe-for-Work…
On the Vulnerability of Text Sanitization
Meng Tong, Kejiang Chen, Xiaojian Yuan +4
Text sanitization, which employs differential privacy to replace sensitive tokens with new ones, represents a significant technique for privacy protection. Typically, its performan…
InferDPT: Privacy-Preserving Inference for Closed-box Large Language Model
Meng Tong, Kejiang Chen, Jie Zhang +5
Large language models (LLMs), like ChatGPT, have greatly simplified text generation tasks. However, they have also raised concerns about privacy risks such as data leakage and unau…