NLM IRP Seminar Schedule
UPCOMING SEMINARS
RECENT SEMINARS
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July 23, 2024 Yu group
Yu Group Research Update -
July 18, 2024 Xiaofang Jiang
Jiang Lab research updates -
May 30, 2024 Deepak Gupta
Towards Answering Health-related Questions from Medical Videos: Datasets and Approaches -
May 28, 2024 Harutyun Saakyan
Simulation of protein fold evolution with atomistic details -
May 23, 2024 Leslie Ronish
Identification of fold-switching proteins by FLIM-FRET
Scheduled Seminars on Feb. 13, 2024
Contact NLM_IRP_Seminar_Scheduling@mail.nih.gov with questions about this seminar.
Abstract:
In this talk, I will present our experience of applying Large Language Models (LLMs) to biomedicine at the BioNLP group. I will first briefly introduce some basics of LLMs, including auto-regressive language modeling, scaling, alignment, few-shot learning, and chain-of-though reasoning. I will share a case study on biomedical question answering for better understanding of these concepts. Despite their great successes, LLMs are known to hallucinate confident-sounding but inaccurate content. In the second part, I will introduce two approaches that augment LLMs to reduce hallucinations in biomedicine, namely retrieval augmentation and tool augmentation. For the former, I will talk about our perspective on how LLMs will impact information seeking from biomedical literature. For the latter, I will present our GeneGPT work for teaching LLMs to use NCBI Web APIs. Finally, with the knowledge gained from the first two parts, I will share our application research, TrialGPT, for patient-to-trial matching with LLMs.