← Search

Maya Kruse

2 accepted papers

2025

Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction

EMNLP 2025

Recent advances in large language models (LLMs) have shown potential in clinical text summarization, but their ability to handle long patient trajectories with multi-modal data spread across time remains underexplored. This study systematically evaluates several state-of-the-art open-source LLMs, th

Cited by 0SourcePDFScholar
2025

Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification

EMNLP 2025

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 calibration and uncertainty quantification often focuses on individual models, overlooking the potential of model diver