most citedAI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies

4 citations · 7 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SE2025

RedCodeAgent: Automatic Red-teaming Agent against Diverse Code Agents

Chengquan Guo, Chulin Xie, Yu Yang +6

Code agents have gained widespread adoption due to their strong code generation capabilities and integration with code interpreters, enabling dynamic execution, debugging, and inte…

cs.CR2025

SIRAJ: Diverse and Efficient Red-Teaming for LLM Agents via Distilled Structured Reasoning

Kaiwen Zhou, Ahmed Elgohary, A S M Iftekhar +1

The ability of LLM agents to plan and invoke tools exposes them to new safety risks, making a comprehensive red-teaming system crucial for discovering vulnerabilities and ensuring…

cs.CR2025★ 1 cited

AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration

Andy Zhou, Kevin Wu, Francesco Pinto +7

As large language models (LLMs) become increasingly capable, security and safety evaluation are crucial. While current red teaming approaches have made strides in assessing LLM vul…

cs.CL2025

Enhancing LLM Safety Through a Theoretical Minimax Game Lens

Yihe Deng, Yu Yang, Junkai Zhang +2

The rapid advancement of large language models (LLMs) necessitates effective mechanisms to ensure their responsible deployment by accurately distinguishing unsafe content from beni…

cs.CR2024★ 1 cited

SeCodePLT: A Unified Platform for Evaluating the Security of Code GenAI

Yuzhou Nie, Zhun Wang, Yu Yang +7

Existing benchmarks for evaluating the security risks and capabilities (e.g., vulnerability detection) of code-generating large language models (LLMs) face several key limitations:…

cs.CY2024★ 1 cited

AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies

Yi Zeng, Yu Yang, Andy Zhou +9

Foundation models (FMs) provide societal benefits but also amplify risks. Governments, companies, and researchers have proposed regulatory frameworks, acceptable use policies, and…

cs.CY2024★ 4 cited

AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies

Yi Zeng, Kevin Klyman, Andy Zhou +6

We present a comprehensive AI risk taxonomy derived from eight government policies from the European Union, United States, and China and 16 company policies worldwide, making a sig…