collaborators

8 papers

cs.CR2026

Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens

Peizhi Niu, Wenjie Qu, Shangding Gu +14

Claw-like AI agents (e.g., OpenClaw) are always-on processes with persistent access to credentials, files, tools, and external services. They take on system-level responsibilities…

cs.CL2026

AgentSPEX: An Agent SPecification and EXecution Language

Pengcheng Wang, Jerry Huang, Jiarui Yao +7

Language-model agent systems commonly rely on reactive prompting, in which a single instruction guides the model through an open-ended sequence of reasoning and tool-use steps, lea…

cs.CR2025

The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search

Rongzhe Wei, Peizhi Niu, Xinjie Shen +7

Large language models (LLMs) remain vulnerable to jailbreak attacks that bypass safety guardrails to elicit harmful outputs. Existing approaches overwhelmingly operate within the p…

cs.AI2025

MCP-Flow: Facilitating LLM Agents to Master Real-World, Diverse and Scaling MCP Tools

Wenhao Wang, Peizhi Niu, Zhao Xu +8

Large Language Models (LLMs) increasingly rely on external tools to perform complex, realistic tasks, yet their ability to utilize the rapidly expanding Model Contextual Protocol (…

cs.CV2025

3DGS-IEval-15K: A Large-scale Image Quality Evaluation Database for 3D Gaussian-Splatting

Yuke Xing, Jiarui Wang, Peizhi Niu +3

3D Gaussian Splatting (3DGS) has emerged as a promising approach for novel view synthesis, offering real-time rendering with high visual fidelity. However, its substantial storage…

cs.LG2025

GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models

Peizhi Niu, Evelyn Ma, Huiting Zhou +4

Unlearning in large language models is becoming increasingly important due to regulatory compliance, copyright protection, and privacy concerns. However, a key challenge in LLM unl…