5 papers
Improving the Distributional Alignment of LLMs using Supervision
Gauri Kambhatla, Sanjana Gautam, Angela Zhang +4
The ability to accurately align LLMs with diverse population groups on subjective questions would have great value. In this work, we show that adding simple supervision can more co…
MedArena: Comparing LLMs for Medicine-in-the-Wild Clinician Preferences
Eric Wu, Kevin Wu, Jason Hom +11
Large language models (LLMs) are increasingly central to clinician workflows, spanning clinical decision support, medical education, and patient communication. However, current eva…
Disentangling Reasoning and Knowledge in Medical Large Language Models
Rahul Thapa, Qingyang Wu, Kevin Wu +11
Medical reasoning in large language models (LLMs) aims to emulate clinicians' diagnostic thinking, but current benchmarks such as MedQA-USMLE, MedMCQA, and PubMedQA often mix reaso…
How Well Can General Vision-Language Models Learn Medicine By Watching Public Educational Videos?
Rahul Thapa, Andrew Li, Qingyang Wu +8
Publicly available biomedical videos, such as those on YouTube, serve as valuable educational resources for medical students. Unlike standard machine learning datasets, these video…
MedCaseReasoning: Evaluating and learning diagnostic reasoning from clinical case reports
Kevin Wu, Eric Wu, Rahul Thapa +7
Doctors and patients alike increasingly use Large Language Models (LLMs) to diagnose clinical cases. However, unlike domains such as math or coding, where correctness can be object…