Paper-Conference

Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
Large language models (LLMs) often behave inconsistently across inputs, indicating uncertainty and motivating the need for its …
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Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction
When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
The introduction of Large Language Models (LLMs) has advanced data representation and analysis, bringing significant progress in their …
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When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
Clinical natural language processing for secondary uses
Learning to Maximize Mutual Information for Chain-of-Thought Distillation
Summarizing Patients’ Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models
Automatically summarizing patients’ main problems from daily progress notes using natural language processing methods helps to battle …
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Summarizing Patients’ Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models
Summarizing Patients’ Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models