4 papers
FragFuse: Bypassing Access Control of Large Language Model Agents via Memory-Based Query Fragmentation and Fusion
Zixin Rao, Wentian Zhu, Chan Aristella Lu +5
Large language model (LLM) agents increasingly rely on long-term memory to support complex task execution, user personalization, and domain adaptation. Meanwhile, emerging access-c…
Green Shielding: A User-Centric Approach Towards Trustworthy AI
Aaron J. Li, Nicolas Sanchez, Hao Huang +8
Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users phrase queries, a gap not well…
CDR-Agent: Intelligent Selection and Execution of Clinical Decision Rules Using Large Language Model Agents
Zhen Xiang, Aliyah R. Hsu, Austin V. Zane +6
Clinical decision-making is inherently complex and fast-paced, particularly in emergency departments (EDs) where critical, rapid and high-stakes decisions are made. Clinical Decisi…
Large Language Model Empowered Privacy-Protected Framework for PHI Annotation in Clinical Notes
Guanchen Wu, Linzhi Zheng, Han Xie +7
The de-identification of private information in medical data is a crucial process to mitigate the risk of confidentiality breaches, particularly when patient personal details are n…