8 citations · 8 across the 10 of their papers we have counts for
10 papers
BiAxisBias: Evaluating LLM Bias Beyond a Single Prompt and a Single Explanation
Jialing Gan, Junhao Dong, Songze Li
LLM bias scores can depend on audit design. We introduce BiAxisBias, a prespecified audit varying task, role, perspective, sentiment, and wording over 200 stereotype statements whi…
CIBER: A Comprehensive Benchmark for Security Evaluation of Code Interpreter Agents
Lei Ba, Qinbin Li, Songze Li
LLM-based code interpreter agents are increasingly deployed in critical workflows, yet their robustness against risks introduced by their code execution capabilities remains undere…
Beauty and the Beast: Imperceptible Perturbations Against Diffusion-Based Face Swapping via Directional Attribute Editing
Yilong Huang, Songze Li
Diffusion-based face swapping achieves state-of-the-art performance, yet it also exacerbates the potential harm of malicious face swapping to violate portraiture right or undermine…
MASH: Evading Black-Box AI-Generated Text Detectors via Style Humanization
Yongtong Gu, Songze Li, Xia Hu
The increasing misuse of AI-generated texts (AIGT) has motivated the rapid development of AIGT detection methods. However, the reliability of these detectors remains fragile agains…
Responsible Diffusion: A Comprehensive Survey on Safety, Ethics, and Trust in Diffusion Models
Kang Wei, Xin Yuan, Fushuo Huo +5
Diffusion models (DMs) have been investigated in various domains due to their ability to generate high-quality data, thereby attracting significant attention. However, similar to t…
FuncPoison: Poisoning Function Library to Hijack Multi-agent Autonomous Driving Systems
Yuzhen Long, Songze Li
Autonomous driving systems increasingly rely on multi-agent architectures powered by large language models (LLMs), where specialized agents collaborate to perceive, reason, and pla…
Policy Disruption in Reinforcement Learning:Adversarial Attack with Large Language Models and Critical State Identification
Junyong Jiang, Buwei Tian, Chenxing Xu +2
Reinforcement learning (RL) has achieved remarkable success in fields like robotics and autonomous driving, but adversarial attacks designed to mislead RL systems remain challengin…
TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement Learning
Mingxuan Zhang, Oubo Ma, Kang Wei +2
Deep reinforcement learning (DRL) has achieved remarkable success in a wide range of sequential decision-making applications, including robotics, healthcare, smart grids, and finan…
LLMs Cannot Reliably Judge (Yet?): A Comprehensive Assessment on the Robustness of LLM-as-a-Judge
Songze Li, Chuokun Xu, Jiaying Wang +6
Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse tasks, driving the development and widespread adoption of LLM-as-a-Judge systems for automate…
Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents
Yuyou Gan, Yong Yang, Zhe Ma +10
With the continuous development of large language models (LLMs), transformer-based models have made groundbreaking advances in numerous natural language processing (NLP) tasks, lea…