I am an Assistant Professor at The School of Digital Humanities and Computational Social Sciences at the Korea Advanced Institute of Science and Technology (KAIST).
As a linguist and syntactician, I explore the principles that underlie complex phenomena involving the structure of natural language. Recently, I have growing interests in the biological underpinnings of these principles, as well as the role of linguistic knowledge in effective and safe use of large language models.
I received my Ph.D. in linguistics at the Department of Linguistics and Philosophy at MIT in 2024.
Before my Ph.D, I studied for a B.A. and M.A. in linguistics at the Department of Linguistics at Seoul National University.
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You can find my CV here.
We study the structure and meaning of natural language, couched within state-of-the-art theoretical development. Uncovering the universal principles and parameters of natural language is the fundamental basis of linguistics and linguistically aligned research. As we tackle our research questions, we aim for both theoretical precision as well as quantitative rigour. This may involve using quantitative methods such as psycholinguistic experiments and corpus analysis.
Large language models are getting better at not only speaking like humans, but also at capturing structural phenomena that were deemed inaccessible to them a few years ago. However, this achievement sits on training data that is orders of magnitude larger than what the average human is exposed to during their childhood. Can we use developmentally plausible language models to probe the human language faculty without extreme data and resource usage?
Our current project funded by the National Research Foundation of Korea aims to develop a framework for detecting implicit bias in LLM output. Unlike explicit bias, implicit bias is harder to detect and appears in subtle ways. We aim to provide a framework for detecting them based on linguistic cues such as coreference resolution. We also aspire to provide a solution that is generalizable to lower-resource languages.