6 papers
Quantifying Hallucinations in Language Language Models on Medical Textbooks
Brandon C. Colelough, Davis Bartels, Dina Demner-Fushman
Hallucinations, the tendency for large language models to provide responses with factually incorrect and unsupported claims, is a serious problem within natural language processing…
Overview of TREC 2025 Biomedical Generative Retrieval (BioGen) Track
Deepak Gupta, Dina Demner-Fushman, William Hersh +2
Recent advances in large language models (LLMs) have made significant progress across multiple biomedical tasks, including biomedical question answering, lay-language summarization…
BioACE: An Automated Framework for Biomedical Answer and Citation Evaluations
Deepak Gupta, Davis Bartels, Dina Demner-Fushman
With the increasing use of large language models (LLMs) for generating answers to biomedical questions, it is crucial to evaluate the quality of the generated answers and the refer…
Lessons from the TREC Plain Language Adaptation of Biomedical Abstracts (PLABA) track
Brian Ondov, William Xia, Kush Attal +3
Objective: Recent advances in language models have shown potential to adapt professional-facing biomedical literature to plain language, making it accessible to patients and caregi…
Overview of the ClinIQLink 2025 Shared Task on Medical Question-Answering
Brandon Colelough, Davis Bartels, Dina Demner-Fushman
In this paper, we present an overview of ClinIQLink, a shared task, collocated with the 24th BioNLP workshop at ACL 2025, designed to stress-test large language models (LLMs) on me…
JEBS: A Fine-grained Biomedical Lexical Simplification Task
William Xia, Ishita Unde, Brian Ondov +1
Online medical literature has made health information more available than ever, however, the barrier of complex medical jargon prevents the general public from understanding it. Th…