13 citations · 20 across the 12 of their papers we have counts for
13 papers · 1 filter
SAGE: Sense-Aligned Multimodal Grounding Evaluation with Gloss-Augmented Reasoning
Sunjae Kwon, Suhaas Kiran DG, Zonghai Yao +3
This paper introduces Sense-Aligned Grounding Evaluation (SAGE), a unified 10-candidate image-selection benchmark that reformulates VWSD, VerSe, and WikiDiverse into a shared term-…
Blocks Architecture (BloArk): Efficient, Cost-Effective, and Incremental Dataset Architecture for Wikipedia Revision History
Lingxi Li, Zonghai Yao, Sunjae Kwon +1
Wikipedia (Wiki) is one of the most widely used and publicly available resources for natural language processing (NLP) applications. Wikipedia Revision History (WikiRevHist) shows…
Large Language Model-based Role-Playing for Personalized Medical Jargon Extraction
Jung Hoon Lim, Sunjae Kwon, Zonghai Yao +2
Previous studies reveal that Electronic Health Records (EHR), which have been widely adopted in the U.S. to allow patients to access their personal medical information, do not have…
ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes
Zhichao Yang, Avijit Mitra, Sunjae Kwon +1
The advancement of natural language processing (NLP) systems in healthcare hinges on language model ability to interpret the intricate information contained within clinical notes.…
README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP
Zonghai Yao, Nandyala Siddharth Kantu, Guanghao Wei +6
The advancement in healthcare has shifted focus toward patient-centric approaches, particularly in self-care and patient education, facilitated by access to Electronic Health Recor…
ODD: A Benchmark Dataset for the Natural Language Processing based Opioid Related Aberrant Behavior Detection
Sunjae Kwon, Xun Wang, Weisong Liu +7
Opioid related aberrant behaviors (ORABs) present novel risk factors for opioid overdose. This paper introduces a novel biomedical natural language processing benchmark dataset nam…
Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information
Sunjae Kwon, Rishabh Garodia, Minhwa Lee +2
Visual Word Sense Disambiguation (VWSD) is a task to find the image that most accurately depicts the correct sense of the target word for the given context. Previously, image-text…
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…
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…
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…
Why Do Neural Language Models Still Need Commonsense Knowledge to Handle Semantic Variations in Question Answering?
Sunjae Kwon, Cheongwoong Kang, Jiyeon Han +1
Many contextualized word representations are now learned by intricate neural network models, such as masked neural language models (MNLMs) which are made up of huge neural network…
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…
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…