2 citations · 4 across the 12 of their papers we have counts for
5 papers · 1 filter
Med-V1: Small Language Models for Zero-shot and Scalable Biomedical Evidence Attribution
Qiao Jin, Yin Fang, Lauren He +12
Assessing whether an article supports an assertion is essential for hallucination detection and claim verification. While large language models (LLMs) have the potential to automat…
EvidenceOutcomes: a Dataset of Clinical Trial Publications with Clinically Meaningful Outcomes
Yiliang Zhou, Abigail M. Newbury, Gongbo Zhang +4
The fundamental process of evidence extraction and synthesis in evidence-based medicine involves extracting PICO (Population, Intervention, Comparison, and Outcome) elements from b…
Semi-Supervised Learning from Small Annotated Data and Large Unlabeled Data for Fine-grained PICO Entity Recognition
Fangyi Chen, Gongbo Zhang, Yilu Fang +2
Objective: Extracting PICO elements -- Participants, Intervention, Comparison, and Outcomes -- from clinical trial literature is essential for clinical evidence retrieval, appraisa…
A MapReduce Approach to Effectively Utilize Long Context Information in Retrieval Augmented Language Models
Gongbo Zhang, Zihan Xu, Qiao Jin +8
While holding great promise for improving and facilitating healthcare, large language models (LLMs) struggle to produce up-to-date responses on evolving topics due to outdated know…
Closing the gap between open-source and commercial large language models for medical evidence summarization
Gongbo Zhang, Qiao Jin, Yiliang Zhou +11
Large language models (LLMs) hold great promise in summarizing medical evidence. Most recent studies focus on the application of proprietary LLMs. Using proprietary LLMs introduces…