91 citations · 155 across the 24 of their papers we have counts for
4 papers · 1 filter
Brittleness and Promise: Knowledge Graph Based Reward Modeling for Diagnostic Reasoning
Saksham Khatwani, He Cheng, Majid Afshar +2
Large language models (LLMs) show promise for diagnostic reasoning but often lack reliable, knowledge grounded inference. Knowledge graphs (KGs), such as the Unified Medical Langua…
Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
Skatje Myers, Dmitriy Dligach, Timothy A. Miller +6
Objective: To evaluate whether retrieval-augmented generation (RAG) can serve as an efficient alternative to long-context prompting for clinical reasoning over electronic health re…
Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
Maya Kruse, Majid Afshar, Saksham Khatwani +3
Large language models (LLMs) often behave inconsistently across inputs, indicating uncertainty and motivating the need for its quantification in high-stakes settings. Prior work on…
Development and Validation of the Provider Documentation Summarization Quality Instrument for Large Language Models
Emma Croxford, Yanjun Gao, Nicholas Pellegrino +16
As Large Language Models (LLMs) are integrated into electronic health record (EHR) workflows, validated instruments are essential to evaluate their performance before implementatio…