Author

Zekun Wen

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#artificial intelligence Preprint Sep 2026

Concealing LLM-Based Multi-Agent Topology via Phantom Structure Injection

Driven by the rapid advancement of large language models (LLMs), LLM-based multi-agent systems (MAS) have emerged as a powerful paradigm for collaborative reasoning over complex tasks. A key design element of MAS is the communication topology, which governs information flow among agents and often encodes proprietary kn...

Long-Zhu He, Ze-Kun Wen, Xin-Feng Li et al. · 0 citations

#machine learning Preprint Aug 2026

Are LLM-Enhanced GNNs Privacy-Safe?

A systematic evaluation of privacy risks in LLM-enhanced GNNs through a unified framework consisting of five stages and reveals that semantic enrichment amplifies link-, label-, and membership-related signals in the embedding space, making them more exploitable by inference attacks.

Long-Zhu He, Ze-Kun Wen, Chao-Zhuo Li et al. · 0 citations