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.

Message

“At Sony AI, I am trying to devote myself to apply natural language processing techniques for achieving the goal of our organization: widening imagination and creativity with AI. I am honored that I can serve on the gastronomy flagship project, the area that is driven by a sophisticated level of creativity, using my knowledge. As a member of Sony AI, I want to reach an unexplored territory of AI research.”

Publications

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…

RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer

CIKM, 2022
Mogan Gim*, Donghee Choi*, Kana Maruyama, Jihun Choi, Hajung Kim*, Donghyeon Park*, Jaewoo Kang*

We propose a computational approach for recipe ideation, a downstream task that helps users select and gather ingredients for creating dishes. To perform this task, we developed RecipeMind, a food affinity score prediction model that quantifies the suitability of adding an i…

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