STAG is proposed, a stealthy trojan attack framework designed for the graph-language alignment interface of GFMs on TAGs that realizes trigger nodes as readable text through candidate retrieval and regularizes the trigger-attached subgraph so that its local structure remains close to the original subgraph.
Min-hua Lin, Zhi-Cheng Gao, Yilong Wang et al.· 0 citations
A novel framework for constructing a Context-Enhanced MMKG (CEMMKG) is proposed, effective in leveraging contextual information to improve MMKG-based RAG performance and its effectiveness across different MMKG-based RAG methods demonstrates its broad applicability.
Zongyu Wu, Yilong Wang, Xiaochen Wang et al.· 0 citations
This survey presents a unified and pipeline-aware overview of RAG robustness, formalize threat models over the corpus, retriever, and generator, and organize attacks into three main objectives: accuracy, privacy, and fairness.
Minh Tran, Cuong Dang, Tuc Nguyen et al.· 1 citation
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