1 citations · 1 across the 5 of their papers we have counts for
10 papers
Making Theft Useless: Adulteration-Based Protection of Proprietary Knowledge Graphs in GraphRAG Systems
Weijie Wang, Peizhuo Lv, Yan Wang +7
Graph Retrieval-Augmented Generation (GraphRAG) has emerged as a key technique for enhancing Large Language Models (LLMs) with proprietary Knowledge Graphs (KGs) in knowledge-inten…
EmoRAG: Evaluating RAG Robustness to Symbolic Perturbations
Xinyun Zhou, Xinfeng Li, Yinan Peng +9
Retrieval-Augmented Generation (RAG) systems are increasingly central to robust AI, enhancing large language model (LLM) faithfulness by incorporating external knowledge. However,…
Mano Technical Report
Tianyu Fu, Anyang Su, Chenxu Zhao +20
Graphical user interfaces (GUIs) are the primary medium for human-computer interaction, yet automating GUI interactions remains challenging due to the complexity of visual elements…
A Vision for Access Control in LLM-based Agent Systems
Xinfeng Li, Dong Huang, Jie Li +5
The autonomy and contextual complexity of LLM-based agents render traditional access control (AC) mechanisms insufficient. Static, rule-based systems designed for predictable envir…
MedSentry: Understanding and Mitigating Safety Risks in Medical LLM Multi-Agent Systems
Kai Chen, Taihang Zhen, Hewei Wang +7
As large language models (LLMs) are increasingly deployed in healthcare, ensuring their safety, particularly within collaborative multi-agent configurations, is paramount. In this…
Feature-Aware Malicious Output Detection and Mitigation
Weilong Dong, Peiguang Li, Yu Tian +3
The rapid advancement of large language models (LLMs) has brought significant benefits to various domains while introducing substantial risks. Despite being fine-tuned through rein…