activity
20182022
most citedBuilding a PubMed knowledge graph

9 citations · 17 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2020

Transferability of Natural Language Inference to Biomedical Question Answering

Minbyul Jeong, Mujeen Sung, Gangwoo Kim +4

Biomedical question answering (QA) is a challenging task due to the scarcity of data and the requirement of domain expertise. Pre-trained language models have been used to address…

cs.DL20209 cited

Building a PubMed knowledge graph

Jian Xu, Sunkyu Kim, Min Song +12

PubMed is an essential resource for the medical domain, but useful concepts are either difficult to extract or are ambiguated, which has significantly hindered knowledge discovery.…

cs.CL2019

Pre-trained Language Model for Biomedical Question Answering

Wonjin Yoon, Jinhyuk Lee, Donghyeon Kim +2

The recent success of question answering systems is largely attributed to pre-trained language models. However, as language models are mostly pre-trained on general domain corpora…

cs.CL2019

BioBERT: a pre-trained biomedical language representation model for biomedical text mining

Jinhyuk Lee, Wonjin Yoon, Sungdong Kim +4

Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting va…

cs.LG2018

Learning User Preferences and Understanding Calendar Contexts for Event Scheduling

Donghyeon Kim, Jinhyuk Lee, Donghee Choi +2

With online calendar services gaining popularity worldwide, calendar data has become one of the richest context sources for understanding human behavior. However, event scheduling…