activity
20242026
most citedLLM-PBE: Assessing Data Privacy in Large Language Models

2 citations · 2 across the 9 of their papers we have counts for

collaborators

14 papers

cs.CR2026

A Framework for Formalizing LLM Agent Security

Vincent Siu, Jingxuan He, Kyle Montgomery +4

Security in LLM agents is inherently contextual. For example, the same action taken by an agent may represent legitimate behavior or a security violation depending on whose instruc…

cs.AI2026

OpenSage: Self-programming Agent Generation Engine

Hongwei Li, Zhun Wang, Qinrun Dai +11

Agent development kits (ADKs) provide effective platforms and tooling for constructing agents, and their designs are critical to the constructed agents' performance, especially the…

cs.CR2026

The Attack and Defense Landscape of Agentic AI: A Comprehensive Survey

Juhee Kim, Xiaoyuan Liu, Zhun Wang +4

AI agents that combine large language models with non-AI system components are rapidly emerging in real-world applications, offering unprecedented automation and flexibility. Howev…

cs.CR2026

WebSentinel: Detecting and Localizing Prompt Injection Attacks for Web Agents

Xilong Wang, Yinuo Liu, Zhun Wang +2

Prompt injection attacks manipulate webpage content to cause web agents to execute attacker-specified tasks instead of the user's intended ones. Existing methods for detecting and…

cs.CR2025

VulnLLM-R: Specialized Reasoning LLM with Agent Scaffold for Vulnerability Detection

Yuzhou Nie, Hongwei Li, Chengquan Guo +5

We propose VulnLLM-R, the~\emph{first specialized reasoning LLM} for vulnerability detection. Our key insight is that LLMs can reason about program states and analyze the potential…

cs.CV2025

VMDT: Decoding the Trustworthiness of Video Foundation Models

Yujin Potter, Zhun Wang, Nicholas Crispino +11

As foundation models become more sophisticated, ensuring their trustworthiness becomes increasingly critical; yet, unlike text and image, the video modality still lacks comprehensi…