7 papers
Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance
Parker Seegmiller, Sarah Masud Preum
LLMs are increasingly deployed in dynamic, real-world settings, where the distribution of user prompts can shift substantially over time as new tasks, prompts, and users are introd…
Medical Triage as Pairwise Ranking: A Benchmark for Urgency in Patient Portal Messages
Joseph Gatto, Parker Seegmiller, Timothy Burdick +4
Medical triage is the task of allocating medical resources and prioritizing patients based on medical need. This paper introduces the first large-scale public dataset for studying…
How Much Would a Clinician Edit This Draft? Evaluating LLM Alignment for Patient Message Response Drafting
Parker Seegmiller, Joseph Gatto, Sarah E. Greer +4
Large language models (LLMs) show promise in drafting responses to patient portal messages, yet their integration into clinical workflows raises various concerns, including whether…
FLAMES: Improving LLM Math Reasoning via a Fine-Grained Analysis of the Data Synthesis Pipeline
Parker Seegmiller, Kartik Mehta, Soumya Saha +6
Recent works improving LLM math reasoning with synthetic data have used unique setups, making comparison of data synthesis strategies impractical. This leaves many unanswered quest…
Follow-up Question Generation For Enhanced Patient-Provider Conversations
Joseph Gatto, Parker Seegmiller, Timothy Burdick +3
Follow-up question generation is an essential feature of dialogue systems as it can reduce conversational ambiguity and enhance modeling complex interactions. Conversational contex…
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…