LARK: NLP & AI Research Lab @ CU
LARK: NLP & AI Research Lab @ CU
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Yanjun Gao
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LogosKG: Hardware-Optimized Scalable and Interpretable Knowledge Graph Retrieval
Race, Ethnicity and Their Implication on Bias in Large Language Models
Anchored Answers: Unravelling Positional Bias in GPT-2's Multiple-Choice Questions
Automating Evaluation of AI Text Generation in Healthcare with a Large Language Model (LLM)-as-a-Judge
Brittleness and Promise: Knowledge Graph Based Reward Modeling for Diagnostic Reasoning
Current and future state of evaluation of large language models for medical summarization tasks
Detecting Stigmatizing Language in Clinical Notes with Large Language Models for Addiction Care
Development and validation of the provider documentation summarization quality instrument for large language models
Evaluating clinical AI summaries with large language models as judges
Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction
Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study
Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability
Uncovering Hidden Violent Tendencies in LLMs: A Demographic Analysis via Behavioral Vignettes
Clinical natural language processing for secondary uses
Development of a Human Evaluation Framework and Correlation with Automated Metrics for Natural Language Generation of Medical Diagnoses
Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review
Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data
Learning to Maximize Mutual Information for Chain-of-Thought Distillation
Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies
On the role of the UMLS in supporting diagnosis generation proposed by Large Language Models
Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability
Prompt Engineering GPT-4 to Answer Patient Inquiries: A Real-Time Implementation in the Electronic Health Record across Provider Clinics
When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
Call for papers: Special issue on clinical natural language processing for secondary use applications.
Summarizing Patients’ Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models
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