most citedMeasuring Agents in Production

3 citations · 3 across the 3 of their papers we have counts for

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.CY20263 cited

Measuring Agents in Production

Melissa Z. Pan, Negar Arabzadeh, Riccardo Cogo +22

LLM-based agents already operate in production across many industries, yet we lack an understanding of what technical methods make deployments successful. We present the first syst…

cs.CR2026

Securing LLM Agents Need Intent-to-Execution Integrity

Wenjie Qu, Ming Xu, Peiran Wang +3

This position paper argues that securing LLM agents requires first defining an end-to-end correctness property that specifies when an agent's execution faithfully reflects the user…

cs.CR2026

CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale

Zhun Wang, Tianneng Shi, Jingxuan He +3

AI agents have significant potential to reshape cybersecurity, making a thorough assessment of their capabilities critical. However, existing evaluations fall short, because they a…

cs.CR2025

Frontier AI's Impact on the Cybersecurity Landscape

Yujin Potter, Wenbo Guo, Zhun Wang +6

The impact of frontier AI (i.e., AI agents and foundation models) in cybersecurity is rapidly increasing. In this paper, we comprehensively analyze this trend through multiple aspe…

cs.AI2025

An Illusion of Progress? Assessing the Current State of Web Agents

Tianci Xue, Weijian Qi, Tianneng Shi +5

As digitalization and cloud technologies evolve, the web is becoming increasingly important in the modern society. Autonomous web agents based on large language models (LLMs) hold…