6 papers
Black-box Membership Inference Attacks on the Pre-training Data of Image-generation Models
Tao Qi, Huili Wang, Yuanhong Huang +6
The rapid advancement of diffusion-based image generation models has raised serious concerns regarding potential copyright and privacy infringements involving human-created data. M…
Black-Box Membership Inference Attack for LVLMs via Prior Knowledge-Calibrated Memory Probing
Jinhua Yin, Peiru Yang, Chen Yang +5
Large vision-language models (LVLMs) derive their capabilities from extensive training on vast corpora of visual and textual data. Empowered by large-scale parameters, these models…
Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness
Peiru Yang, Xintian Li, Wanchun Ni +6
Recent advancements in watermarking techniques have enabled the embedding of secret messages into AI-generated text (AIGT), serving as an important mechanism for AIGT detection. Ex…
MrM: Black-Box Membership Inference Attacks against Multimodal RAG Systems
Peiru Yang, Jinhua Yin, Haoran Zheng +7
Multimodal retrieval-augmented generation (RAG) systems enhance large vision-language models by integrating cross-modal knowledge, enabling their increasing adoption across real-wo…
HeteRAG: A Heterogeneous Retrieval-augmented Generation Framework with Decoupled Knowledge Representations
Peiru Yang, Xintian Li, Zhiyang Hu +8
Retrieval-augmented generation (RAG) methods can enhance the performance of LLMs by incorporating retrieved knowledge chunks into the generation process. In general, the retrieval…
Evidencing Unauthorized Training Data from AI Generated Content using Information Isotopes
Qi Tao, Yin Jinhua, Cai Dongqi +10
In light of scaling laws, many AI institutions are intensifying efforts to construct advanced AIs on extensive collections of high-quality human data. However, in a rush to stay co…