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Gated Activation Steering for Reducing Sycophancy & Hallucination in Medical Question Answering
Himanshu Tripathi, Subash Neupane, Shaswata Mitra +3
Sycophancy and hallucination are persistent failure modes of Large Language Models (LLMs) across domains. However, it becomes particularly consequential in clinical question answer…
Algorithm Design and Physician Liability
Shujie Luan, Shubhranshu Singh, Tinglong Dai
A single clinical algorithm can deliver unequal accuracy across patient groups, and concern about such disparity has grown as artificial intelligence (AI) spreads through clinical…
R-GAT: Cancer Document Classification Leveraging Graph-Based Residual Network for Scenarios with Limited Data
Elias Hossain, Tasfia Nuzhat, Shamsul Masum +2
Accurate classification of cancer-related biomedical abstracts is critical for advancing cancer informatics and supporting decision-making in healthcare research. Yet progress in t…
LLMZ+: Contextual Prompt Whitelist Principles for Agentic LLMs
Tom Pawelek, Raj Patel, Charlotte Crowell +4
Compared to traditional models, agentic AI represents a highly valuable target for potential attackers as they possess privileged access to data sources and API tools, which are tr…
Patient-Centric Knowledge Graphs: A Survey of Current Methods, Challenges, and Applications
Hassan S. Al Khatib, Subash Neupane, Harish Kumar Manchukonda +4
Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that focuses on individualized patient care by mapping the patient's health information in a hol…