5 papers
Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
Xiao Xiang, David Restrepo, Hyewon Jeong +2
Electronic health records (EHR) arrive masked. Clinicians order measurements selectively, and any patient table thus contains only a subset of the values that characterize the unde…
Robustness Beyond Known Groups with Low-rank Adaptation
Abinitha Gourabathina, Hyewon Jeong, Teya Bergamaschi +2
Deep learning models trained to optimize average accuracy often exhibit systematic failures on particular subpopulations. In real world settings, the subpopulations most affected b…
LEMoN: Label Error Detection using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole +4
Large repositories of image-caption pairs are essential for the development of vision-language models. However, these datasets are often extracted from noisy data scraped from the…
MedPAIR: Measuring Physicians and AI Relevance Alignment in Medical Question Answering
Yuexing Hao, Kumail Alhamoud, Hyewon Jeong +6
Large Language Models (LLMs) have demonstrated remarkable performance on various medical question-answering (QA) benchmarks, including standardized medical exams. However, correct…
RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data
Maxwell A. Xu, Jaya Narain, Gregory Darnell +7
We present RelCon, a novel self-supervised Relative Contrastive learning approach for training a motion foundation model from wearable accelerometry sensors. First, a learnable dis…