1 citations · 2 across the 8 of their papers we have counts for
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Sense and Sensitivity: Benchmarking LLM Clinical Triage Recommendations with Physician Experts
Abinitha Gourabathina, Haoran Zhang, Yuexing Hao +2
As large language models (LLMs) are increasingly used in clinical settings, it is critical to evaluate their reliability under realistic variation in clinical text. We study this q…
Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification
Kimia Hamidieh, Veronika Thost, Walter Gerych +2
Large language models (LLMs) often produce confident yet incorrect responses, and uncertainty quantification is one potential solution to more robust usage. Recent works routinely…
The MedPerturb Dataset: What Non-Content Perturbations Reveal About Human and Clinical LLM Decision Making
Abinitha Gourabathina, Yuexing Hao, Walter Gerych +1
Clinical robustness is critical to the safe deployment of medical Large Language Models (LLMs), but key questions remain about how LLMs and humans may differ in response to the rea…