Jaehyun Nam

Ph.D. student at KAIST

KAIST AI

jaehyun.nam [AT] kaist.ac.kr

About

I am a Ph.D. student at KAIST, advised by Prof. Jinwoo Shin. My research interest interests lies in developing effective tabular learning frameworks for handling tabular prediction tasks. In particular, my recent research focuses on integrating large language models into the tabular learning framework using LLM's capabilities such as in-context learning and LLM as an optimization tool.

Topics of interest (publications with overlap):

Publications

(*: Equal contribution)

An Efficient Tokenization for Molecular Language Models

Seojin Kim, Jaehyun Nam, Jinwoo Shin

Preprint, 2024

Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning

Jaehyun Nam*, Kyuyoung Kim*, Seunghyuk Oh, Jihoon Tack, Jaehyung Kim, Jinwoo Shin

Conference on Neural Information Processing Systems (NeurIPS), 2024

Tabular Transfer Learning via Prompting LLMs

Jaehyun Nam, Woomin Song, Seong Hyeon Park, Jihoon Tack, Sukmin Yun, Jaehyung Kim, Kyu Hwan Oh, Jinwoo Shin

Conference on Language Modeling (COLM), 2024

ICML Workshop on Efficient Systems for Foundation Models (ICMLW-ES-FoMo), 2023

Data-Efficient Molecular Generation with Hierarchical Textual Inversion

Seojin Kim, Jaehyun Nam, Sihyun Yu, Younghoon Shin, Jinwoo Shin

International Conference on Machine Learning (ICML), 2024

NeurIPS Workshop on New Frontiers of AI for Drug Discovery and Development (NeurIPSW-AI4D3), 2023

Holistic Molecular Representation Learning via Multi-view Fragmentation

Seojin Kim*, Jaehyun Nam*, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin

Transactions on Machine Learning Research (TMLR), 2024

ICLR Workshop on Machine Learning for Materials (ICLRW-ML4Materials), 2023

SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs

Jaehyung Kim, Jaehyun Nam, Sangwoo Mo, Jongjin Park, Sang-Woo Lee, Minjoon Seo, Jung-Woo Ha, Jinwoo Shin

International Conference on Learning Representations (ICLR), 2024

STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin

International Conference on Learning Representations (ICLR), 2023, Spotlight Presentation (280/4956=5.6%)

NeurIPS Workshop on Table Representation Learning (NeurIPSW-TRL), 2022

Bronze Prize, Samsung Humantech Paper Awards, 2023

Recipient, Google Conference Scholarships (APAC), 2023

Travel Award, International Conference on Learning Representations (ICLR), 2023

Grand Prize, KAIST-Samsung Electronics Industry-Academia Cooperation Paper Award, 2023

An Efficient Tokenization for Molecular Language Models

Seojin Kim, Jaehyun Nam, Jinwoo Shin

Preprint, 2024

Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning

Jaehyun Nam*, Kyuyoung Kim*, Seunghyuk Oh, Jihoon Tack, Jaehyung Kim, Jinwoo Shin

Conference on Neural Information Processing Systems (NeurIPS), 2024

Tabular Transfer Learning via Prompting LLMs

Jaehyun Nam, Woomin Song, Seong Hyeon Park, Jihoon Tack, Sukmin Yun, Jaehyung Kim, Kyu Hwan Oh, Jinwoo Shin

Conference on Language Modeling (COLM), 2024

Data-Efficient Molecular Generation with Hierarchical Textual Inversion

Seojin Kim, Jaehyun Nam, Sihyun Yu, Younghoon Shin, Jinwoo Shin

International Conference on Machine Learning (ICML), 2024

Holistic Molecular Representation Learning via Multi-view Fragmentation

Seojin Kim*, Jaehyun Nam*, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin

Transactions on Machine Learning Research (TMLR), 2024

SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs

Jaehyung Kim, Jaehyun Nam, Sangwoo Mo, Jongjin Park, Sang-Woo Lee, Minjoon Seo, Jung-Woo Ha, Jinwoo Shin

International Conference on Learning Representations (ICLR), 2024

STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin

International Conference on Learning Representations (ICLR), 2023, Spotlight Presentation (280/4956=5.6%)

Education

Korea Advanced Institute of Science and Technology (KAIST)

Ph.D. in Artificial IntelligenceSep. 2023 - Present

M.S. in Artificial IntelligenceMar. 2022 - Aug. 2023

Seoul National University (SNU)

B.S. in Industrial Engineering and Mathematical Sciences (minor)Mar. 2016 - Feb. 2022

Experience

Seoul National University (SNU)Mar. 2021 - Feb. 2022

Research Intern, hosted by Prof. Jung Hee Cheon

Korea Advanced Institute of Science and Technology (KAIST)Dec. 2020 - Jun. 2021

Research Intern, hosted by Prof. Chanyoung Park

SK HynixDec. 2020 - Feb. 2021

Intern, AI Solution

Industrial & Mathematical Data Analytics Research Center (IMDARC)Sep. 2020 - Dec. 2020

Research Intern, hosted by Prof. Woong Kook

Honors and Awards

Grand Prize ($5,000), KAIST-Samsung Electronics Industry-Academia Cooperation Paper Award Aug. 2023

Travel Award ($1,000), International Conference on Learning Representations (ICLR) May. 2023

Recipient ($3,000), Google Conference Scholarships (APAC) May. 2023

Bronze Prize ($5,000), Samsung Humantech Paper Awards Feb. 2023

Special Prize ($1,000), National Cryptograpy Contest Oct. 2021

Recipient ($6,000), Hanseong Scholarship for Gifted Students 2014 - 2016

Academic Services

Conference Reviewer NeurIPS'24

Workshop Reviewer TRL@NeurIPS'23

Invited Talks

Semi-supervised Tabular Classification via In-context Learning of Large Language Models

Samsung Advanced Institue of Technology (Suwon, Korea)Jun. 2023

STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

AI Expo Korea (Seoul, Korea)May. 2023

International Conference on Learning Representations (Kigali, Rwanda)May. 2023

Samsung Electronics Co., Ltd. (Virtual)Mar. 2023

MOGAM Institute for Biomedical Research (Virtual)Mar. 2023

Privacy-preserving Median Selection and Secure Aggregation in Federated Learning

Korean Mathematical Society Fall Meeting (Virtual)Oct. 2021

Special Prize, National Cryptography Contest, 2021