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Anoop Mayampurath

Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
Detecting Stigmatizing Language in Clinical Notes with Large Language Models for Addiction Care
Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability
Development of a Human Evaluation Framework and Correlation with Automated Metrics for Natural Language Generation of Medical Diagnoses
Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies
Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability

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