most citedWhy Do Masked Neural Language Models Still Need Common Sense Knowledge?

13 citations · 16 across the 3 of their papers we have counts for

collaborators
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2022

Multi-label Few-shot ICD Coding as Autoregressive Generation with Prompt

Zhichao Yang, Sunjae Kwon, Zonghai Yao +1

Automatic International Classification of Diseases (ICD) coding aims to assign multiple ICD codes to a medical note with an average of 3,000+ tokens. This task is challenging due t…

cs.CL20223 cited

An Automatic SOAP Classification System Using Weakly Supervision And Transfer Learning

Sunjae Kwon, Zhichao Yang, Hong Yu

In this paper, we introduce a comprehensive framework for developing a machine learning-based SOAP (Subjective, Objective, Assessment, and Plan) classification system without manua…

cs.CL2022

MedJEx: A Medical Jargon Extraction Model with Wiki's Hyperlink Span and Contextualized Masked Language Model Score

Sunjae Kwon, Zonghai Yao, Harmon S. Jordan +3

This paper proposes a new natural language processing (NLP) application for identifying medical jargon terms potentially difficult for patients to comprehend from electronic health…

cs.CL201913 cited

Why Do Masked Neural Language Models Still Need Common Sense Knowledge?

Sunjae Kwon, Cheongwoong Kang, Jiyeon Han +1

Currently, contextualized word representations are learned by intricate neural network models, such as masked neural language models (MNLMs). The new representations significantly…

cs.CL2019

Word Sense Disambiguation using Knowledge-based Word Similarity

Sunjae Kwon, Dongsuk Oh, Youngjoong Ko

In natural language processing, word-sense disambiguation (WSD) is an open problem concerned with identifying the correct sense of words in a particular context. To address this pr…