activity
20242026
most citedMedHELM: Holistic Evaluation of Large Language Models for Medical Tasks

10 citations · 12 across the 10 of their papers we have counts for

collaborators

10 papers

cs.AI2026

Metric Match: A Subset Selection Approach to Evaluating LLM Judge Reliability

Alyssa Unell, Natalie Dullerud, Naomi Boneh +4

LLM judges are used to reduce the need for costly human labor in evaluating open-ended text generation. However, the reliability of these judges depends critically on their alignme…

cs.AI2026

Deployment-Centered Evaluation: Predicting Query-Level Rejection Risk in a Clinical LLM System

Alyssa Unell, Miguel Fuentes, Brenna Li +4

Large language models (LLMs) are increasingly integrated into clinical systems, making it essential to evaluate the real-world utility of these systems. However, static benchmarks…

cs.HC2026

Not Another EHR: Reimagining Physician Information Needs with Generative AI Technology

Ruican Zhong, Jiachen Li, Gary Hsieh +15

Electronic health records (EHRs) have improved data accessibility but have also introduced cognitive burden for physicians, given the sheer volume and complexity of the data involv…

cs.CY2026★ 2 cited

Adoption and Use of LLMs at an Academic Medical Center

Nigam H. Shah, Nerissa Ambers, Abby Pandya +55

While large language models (LLMs) can support clinical documentation needs, standalone tools struggle with "workflow friction" from manual data entry. We developed ChatEHR, a syst…

cs.LG2025

DISCO: A Browser-Based Privacy-Preserving Framework for Distributed Collaborative Learning

Julien T. T. Vignoud, Valérian Rousset, Hugo El Guedj +28

Data is often impractical to share for a range of well considered reasons, such as concerns over privacy, intellectual property, and legal constraints. This not only fragments the…

cs.CL2025

Structured Prompts Improve Evaluation of Language Models

Asad Aali, Muhammad Ahmed Mohsin, Vasiliki Bikia +15

As language models (LMs) are increasingly adopted across domains, high-quality benchmarking frameworks are essential for guiding deployment decisions. In practice, however, framewo…

cs.LG2025

CancerGUIDE: Cancer Guideline Understanding via Internal Disagreement Estimation

Alyssa Unell, Noel C. F. Codella, Sam Preston +13

The National Comprehensive Cancer Network (NCCN) provides evidence-based guidelines for cancer treatment. Translating complex patient presentations into guideline-compliant treatme…

cs.CL2025★ 10 cited

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks

Suhana Bedi, Hejie Cui, Miguel Fuentes +78

While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinica…

cs.AI2025

TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records

Hejie Cui, Alyssa Unell, Bowen Chen +4

Large language models (LLMs) have emerged as promising tools for assisting in medical tasks, yet processing Electronic Health Records (EHRs) presents unique challenges due to their…

cs.LG2024

Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations

Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai +10

Maximum Manifold Capacity Representations (MMCR) is a recent multi-view self-supervised learning (MVSSL) method that matches or surpasses other leading MVSSL methods. MMCR is intri…