15 citations · 19 across the 6 of their papers we have counts for
6 papers
Do AI chatbots find what experts would? Effects of model, user role, and sample size on study retrieval for medical questions
Qingfang Liu, Qiao Jin, Joe D. Menke +2
Large language model (LLM) chatbots are increasingly used to answer clinical questions with citations to relevant studies, yet the quality of retrieved evidence and factors influen…
GenLARP: Enabling Immersive Live Action Role-Play through LLM-Generated Worlds and Characters
Yichen Yu, Yifan Jiang, Mandy Lui +1
We introduce GenLARP, a virtual reality (VR) system that transforms personalized stories into immersive live action role-playing (LARP) experiences. GenLARP enables users to act as…
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healthcare, large language models (LLMs) struggle to produce up-to-date responses on evolving topics due to outdated know…
A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor?
Yunfei Xie, Juncheng Wu, Haoqin Tu +6
Large language models (LLMs) have exhibited remarkable capabilities across various domains and tasks, pushing the boundaries of our knowledge in learning and cognition. The latest…
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…
Leveraging Generative AI for Clinical Evidence Summarization Needs to Ensure Trustworthiness
Gongbo Zhang, Qiao Jin, Denis Jered McInerney +11
Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence. The rapid growth of medical ev…