17 citations · 54 across the 6 of their papers we have counts for
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cs.CL2023★ 16 cited
Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events
Yu Gu, Sheng Zhang, Naoto Usuyama +8
Large language models (LLMs), such as GPT-4, have demonstrated remarkable capabilities across a wide range of tasks, including health applications. In this paper, we study how LLMs…
cs.CL2023★ 4 cited
Few-shot In-context Learning for Knowledge Base Question Answering
Tianle Li, Xueguang Ma, Alex Zhuang +3
Question answering over knowledge bases is considered a difficult problem due to the challenge of generalizing to a wide variety of possible natural language questions. Additionall…
cs.CL2021★ 17 cited
Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing
Robert Tinn, Hao Cheng, Yu Gu +5
Motivation: A perennial challenge for biomedical researchers and clinical practitioners is to stay abreast with the rapid growth of publications and medical notes. Natural language…