732 citations · 809 across the 3 of their papers we have counts for
3 papers
cs.CL2020★ 64 cited
What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Di Jin, Eileen Pan, Nassim Oufattole +3
Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community. In this work, we present t…
cs.CL2019★ 13 cited
MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension
Di Jin, Shuyang Gao, Jiun-Yu Kao +2
Machine Reading Comprehension (MRC) for question answering (QA), which aims to answer a question given the relevant context passages, is an important way to test the ability of int…
cs.CL2019★ 732 cited
Publicly Available Clinical BERT Embeddings
Emily Alsentzer, John R. Murphy, Willie Boag +4
Contextual word embedding models such as ELMo (Peters et al., 2018) and BERT (Devlin et al., 2018) have dramatically improved performance for many natural language processing (NLP)…