30 citations · 55 across the 4 of their papers we have counts for
6 papers
Overview of TREC 2024 Biomedical Generative Retrieval (BioGen) Track
Deepak Gupta, Dina Demner-Fushman, William Hersh +2
With the advancement of large language models (LLMs), the biomedical domain has seen significant progress and improvement in multiple tasks such as biomedical question answering, l…
Refocusing on Relevance: Personalization in NLG
Shiran Dudy, Steven Bedrick, Bonnie Webber
Many NLG tasks such as summarization, dialogue response, or open domain question answering focus primarily on a source text in order to generate a target response. This standard ap…
Searching for Scientific Evidence in a Pandemic: An Overview of TREC-COVID
Kirk Roberts, Tasmeer Alam, Steven Bedrick +6
We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COV…
Are Some Words Worth More than Others?
Shiran Dudy, Steven Bedrick
Current evaluation metrics for language modeling and generation rely heavily on the accuracy of predicted (or generated) words as compared to a reference ground truth. While import…
TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick +6
TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pand…
CREATE: Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records using OMOP Common Data Model
Sijia Liu, Yanshan Wang, Andrew Wen +6
Background: Widespread adoption of electronic health records (EHRs) has enabled secondary use of EHR data for clinical research and healthcare delivery. Natural language processing…