Jihun Choi
Profile
Jihun’s research interest lies in natural language processing and machine learning. He received his Ph.D. and B.S. degree in 2020 and 2014 from the Department of Computer Science, Seoul National University. During his Ph.D. study, his major interest was encoding sentences by extracting their semantics and syntax automatically via deep neural network.
Publications
Literature-based Hypothesis Generation: Predicting the evolution of scientific literature to support scientists
AI4X, 2025 | Tarek R Besold, Uchenna Akujuobi, Samy Badreddine, Jihun Choi, Hatem ElShazly, Frederick Gifford, Kana Maruyama, Kae Nagano, Pablo Sanchez Martin, Thiviyan Thanapalasingam, Alessandra Toniato, Christoph Wehner
Science is advancing at an increasingly quick pace, as evidenced, for instance, by the exponential growth in the number of published research articles per year [1]. On the one hand, this poses anincreasingly pressing challenge: Effectively navigating this ever-growing body o...
Link prediction for hypothesis generation: an active curriculum learning infused temporal graph-based approach
AIR, 2024 | Uchenna Akujuobi, Priyadarshini Kumari, Jihun Choi, Samy Badreddine, Kana Maruyama, Sucheendra K Palaniappan*, Tarek R Besold
Over the last few years Literature-based Discovery (LBD) has regained popularity as a means to enhance the scientific research process. The resurgent interest has spurred the development of supervised and semi-supervised machine learning models aimed at making previously imp...
Analysis of Multi-Source Language Training in Cross-Lingual Transfer
ACL, 2024 | Seong Hoon Lim*, Taejun Yun*, Jinhyeon Kim*, Jihun Choi, Taeuk Kim
The successful adaptation of multilingual language models (LMs) to a specific language-task pair critically depends on the availability of data tailored for that condition. While cross-lingual transfer (XLT) methods have contributed to addressing this data scarcity problem, ...
CookingSense: A Culinary Knowledgebase with Multidisciplinary Assertions
LREC-COLING, 2024 | Donghee Choi*, Mogan Gim*, Donghyeon Park*, Mujeen Sung, Hyunjae Kim, Jaewoo Kang*, Jihun Choi
This paper introduces CookingSense, a descriptive collection of knowledge assertions in the culinary domain extracted from various sources, including web data, scientific papers, and recipes, from which knowledge covering a broad range of aspects is acquired. CookingSense is...