no code implementations • 2 Mar 2024 • Jiho Kim, Ray C. Flanagan, Noelle E. Haviland, ZeAi Sun, Souad N. Yakubu, Edom A. Maru, Kenneth C. Arnold
Large language models (LLMs) are shaping a new user interface (UI) paradigm in writing tools by enabling users to generate text through prompts.
1 code implementation • 21 Jan 2024 • Jawook Gu, Han-Cheol Cho, Jiho Kim, Kihyun You, Eun Kyoung Hong, Byungseok Roh
Moreover, models using expert-annotated data are limited by data scarcity and pre-defined classes, impacting their performance, flexibility and scalability.
1 code implementation • 20 Oct 2023 • Kihyun You, Jawook Gu, Jiyeon Ham, Beomhee Park, Jiho Kim, Eun Kyoung Hong, Woonhyunk Baek, Byungseok Roh
In this paper, we tackle the lack of image-text data in chest X-ray by expanding image-label pair as image-text pair via general prompt and utilizing multiple images and multiple sections in a radiologic report.
1 code implementation • 17 Oct 2023 • Jiho Kim, Yeonsu Kwon, Yohan Jo, Edward Choi
While large language models (LLMs) have made considerable advancements in understanding and generating unstructured text, their application in structured data remains underexplored.
1 code implementation • 11 May 2023 • Jiho Kim, Sungjin Park, Yeonsu Kwon, Yohan Jo, James Thorne, Edward Choi
KGs can be a valuable knowledge source in fact verification due to their reliability and broad applicability.
1 code implementation • 9 Mar 2023 • Hyunseung Chung, Jiho Kim, Joon-Myoung Kwon, Ki-Hyun Jeon, Min Sung Lee, Edward Choi
We compare the performance of our model with other representative models in text-to-speech and text-to-image.
1 code implementation • 18 Mar 2022 • Sungjin Park, Seongsu Bae, Jiho Kim, Tackeun Kim, Edward Choi
MedGTX uses a novel graph encoder to exploit the graphical nature of structured EHR data, and a text encoder to handle unstructured text, and a cross-modal encoder to learn a joint representation space.
no code implementations • 14 Nov 2021 • Seongsu Bae, Daeyoung Kim, Jiho Kim, Edward Choi
An intelligent machine that can answer human questions based on electronic health records (EHR-QA) has a great practical value, such as supporting clinical decisions, managing hospital administration, and medical chatbots.
no code implementations • COLING 2018 • Eun-Kyung Kim, Kijong Han, Jiho Kim, Key-Sun Choi
This demo deals with the problem of capturing omitted arguments in relation extraction given a proper knowledge base for entities of interest.
1 code implementation • COLING 2018 • Sangha Nam, Eun-Kyung Kim, Jiho Kim, Yoosung Jung, Kijong Han, Key-Sun Choi
The increased demand for structured knowledge has created considerable interest in knowledge extraction from natural language sentences.