54 citations · 57 across the 5 of their papers we have counts for
5 papers
ContextLeak: Exfiltrating LLM Agent Context via Malicious Tools
Yuqi Jia, Ruiqi Wang, Patrick Li +3
Exfiltrating an LLM agent's runtime context -- such as the user prompt, execution trajectory, and tool list -- poses severe security and privacy risks to users. Such attacks can be…
AlignSentinel: Alignment-Aware Detection of Prompt Injection Attacks
Yuqi Jia, Ruiqi Wang, Xilong Wang +2
Prompt injection attacks insert malicious instructions into an LLM's input to steer it toward an attacker-chosen task instead of the intended one. Existing detection defenses typic…
CausalTAD: Injecting Causal Knowledge into Large Language Models for Tabular Anomaly Detection
Ruiqi Wang, Ruikang Liu, Runyu Chen +4
Detecting anomalies in tabular data is critical for many real-world applications, such as credit card fraud detection. With the rapid advancements in large language models (LLMs),…
Causal Evaluation of Language Models
Sirui Chen, Bo Peng, Meiqi Chen +7
Causal reasoning is viewed as crucial for achieving human-level machine intelligence. Recent advances in language models have expanded the horizons of artificial intelligence acros…
Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems
Hao-Fei Cheng, Logan Stapleton, Ruiqi Wang +4
Recent work in fair machine learning has proposed dozens of technical definitions of algorithmic fairness and methods for enforcing these definitions. However, we still lack an und…