1 citations · 1 across the 3 of their papers we have counts for
4 papers
Latent Knowledge as a Predictor of Fact Acquisition in Fine-Tuned Large Language Models
Daniel B. Hier, Tayo Obafemi-Ajayi
Large language models store biomedical facts with uneven strength after pretraining: some facts are present in the weights but are not reliably accessible under deterministic decod…
From Memorization to Generalization: Fine-Tuning Large Language Models for Biomedical Term-to-Identifier Normalization
Suswitha Pericharla, Daniel B. Hier, Tayo Obafemi-Ajayi
Effective biomedical data integration depends on automated term normalization, the mapping of natural language biomedical terms to standardized identifiers. This linking of terms t…
Predicting Failures of LLMs to Link Biomedical Ontology Terms to Identifiers Evidence Across Models and Ontologies
Daniel B. Hier, Steven Keith Platt, Tayo Obafemi-Ajayi
Large language models often perform well on biomedical NLP tasks but may fail to link ontology terms to their correct identifiers. We investigate why these failures occur by analyz…
Efficient Standardization of Clinical Notes using Large Language Models
Daniel B. Hier, Michael D. Carrithers, Thanh Son Do +1
Clinician notes are a rich source of patient information but often contain inconsistencies due to varied writing styles, colloquialisms, abbreviations, medical jargon, grammatical…