4 papers
When AI Agents Collude Online: Financial Fraud Risks by Collaborative LLM Agents on Social Platforms
Qibing Ren, Zhijie Zheng, Jiaxuan Guo +3
In this work, we study the risks of collective financial fraud in large-scale multi-agent systems powered by large language model (LLM) agents. We investigate whether agents can co…
Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
Shanghai AI Lab, :, Xiaoyang Chen +35
To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, this report presents a comprehensive assessment of their frontier…
When Autonomy Goes Rogue: Preparing for Risks of Multi-Agent Collusion in Social Systems
Qibing Ren, Sitao Xie, Longxuan Wei +4
Recent large-scale events like election fraud and financial scams have shown how harmful coordinated efforts by human groups can be. With the rise of autonomous AI systems, there i…
LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts
Qibing Ren, Hao Li, Dongrui Liu +7
Safety concerns in large language models (LLMs) have gained significant attention due to their exposure to potentially harmful data during pre-training. In this paper, we identify…