most citedMCP-Guard: A Multi-Stage Defense-in-Depth Framework for Securing Model Context Protocol in Agentic AI

1 citations · 1 across the 11 of their papers we have counts for

collaborators

12 papers

cs.AI2026

FIDES: Faithful Inference via Deep Evidence Signals for Retrieval-Memory Conflict in RAG

Zhe Yu, Wenpeng Xing, Tiancheng Zhao +3

When retrieved evidence contradicts parametric memory, language models frequently ignore context and default to memorized priors -- a failure that undermines the core purpose of re…

cs.AI2026

Silencing the Guardrails: Inference-Time Jailbreaking via Dynamic Contextual Representation Ablation

Wenpeng Xing, Moran Fang, Guangtai Wang +2

While Large Language Models (LLMs) have achieved remarkable performance, they remain vulnerable to jailbreak attacks that circumvent safety constraints. Existing strategies, rangin…

cs.LG2026

MO-RiskVAE: A Multi-Omics Variational Autoencoder for Survival Risk Modeling in Multiple MyelomaMO-RiskVAE

Zixuan Chen, Heng Zhang, YuPeng Qin +5

Multimodal variational autoencoders (VAEs) have emerged as a powerful framework for survival risk modeling in multiple myeloma by integrating heterogeneous omics and clinical data.…

cs.DC2025

DIAP: A Decentralized Agent Identity Protocol with Zero-Knowledge Proofs and a Hybrid P2P Stack

Yuanjie Liu, Wenpeng Xing, Ye Zhou +3

The absence of a fully decentralized, verifiable, and privacy-preserving communication protocol for autonomous agents remains a core challenge in decentralized computing. Existing…

cs.CR2025

Web Fraud Attacks Against LLM-Driven Multi-Agent Systems

Dezhang Kong, Hujin Peng, Yilun Zhang +5

With the proliferation of LLM-driven multi-agent systems (MAS), the security of Web links has become a critical concern. Once MAS is induced to trust a malicious link, attackers ca…

cs.CV2025

CoDe-NeRF: Neural Rendering via Dynamic Coefficient Decomposition

Wenpeng Xing, Jie Chen, Zaifeng Yang +5

Neural Radiance Fields (NeRF) have shown impressive performance in novel view synthesis, but challenges remain in rendering scenes with complex specular reflections and highlights.…

cs.CV2025

UW-3DGS: Underwater 3D Reconstruction with Physics-Aware Gaussian Splatting

Wenpeng Xing, Jie Chen, Zaifeng Yang +5

Underwater 3D scene reconstruction faces severe challenges from light absorption, scattering, and turbidity, which degrade geometry and color fidelity in traditional methods like N…

cs.CL2025

SproutBench: A Benchmark for Safe and Ethical Large Language Models for Youth

Wenpeng Xing, Lanyi Wei, Haixiao Hu +5

The rapid proliferation of large language models (LLMs) in applications targeting children and adolescents necessitates a fundamental reassessment of prevailing AI safety framework…

cs.CR2025★ 1 cited

MCP-Guard: A Multi-Stage Defense-in-Depth Framework for Securing Model Context Protocol in Agentic AI

Wenpeng Xing, Zhonghao Qi, Yupeng Qin +6

While Large Language Models (LLMs) have achieved remarkable performance, they remain vulnerable to jailbreak. The integration of Large Language Models (LLMs) with external tools vi…

cs.AI2025

HGMF: A Hierarchical Gaussian Mixture Framework for Scalable Tool Invocation within the Model Context Protocol

Wenpeng Xing, Zhipeng Chen, Changting Lin +1

Invoking external tools enables Large Language Models (LLMs) to perform complex, real-world tasks, yet selecting the correct tool from large, hierarchically-structured libraries re…

cs.CL2025

Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs

Hongming Yang, Shi Lin, Jun Shao +4

Lightweight Large Language Models (LwLLMs) are reduced-parameter, optimized models designed to run efficiently on consumer-grade hardware, offering significant advantages in resour…

cs.LG2025

NeuRel-Attack: Neuron Relearning for Safety Disalignment in Large Language Models

Yi Zhou, Wenpeng Xing, Dezhang Kong +2

Safety alignment in large language models (LLMs) is achieved through fine-tuning mechanisms that regulate neuron activations to suppress harmful content. In this work, we propose a…