Jungsoo Park
Ph.D. Student, Georgia Tech
School of Interactive Computing
Coda S1153A
jpark3272 [AT] gatech.edu
About
Hello! I am a Ph.D. student in the School of Interactive Computing at Georgia Tech, advised by Alan Ritter. Before starting my Ph.D., I worked as an Applied Scientist at NAVER Clova, where I contributed to the development of a vision-language foundation model, HyperCLOVA X Vision. I received my B.E. in Statistics, B.S. in Computer Science & Engineering, and M.E. in Software from Korea University.
My research focuses on AI for science with large language models. I am particularly interested in two directions: extracting actionable knowledge from scientific corpora, and improving information-to-decision capabilities through numeric prediction of scientific quantities. More broadly, I study reinforcement learning and post-training methods for improving these abilities, as well as reasoning from expert solutions and tool use, which are important components of AI systems for scientific discovery.
Education
Georgia Institute of Technology Atlanta, GA, USA
Ph.D. in Computer Science Aug. 2024 - Present
Advisor: Alan Ritter
Korea University Seoul, Korea
M.E. in Computer Science & Engineering Mar. 2019 - Aug. 2021
Advisor: Jaewoo Kang
Korea University Seoul, Korea
B.E. in Statistics, B.S. in Computer Science & Engineering Mar. 2013 - Feb. 2019
Magna Cum Laude
Research Experience
Georgia Institute of Technology Atlanta, GA, USA
Graduate Research Assistant (Ph.D.) Aug. 2024 - Present
Advisor: Alan Ritter
Naver Clova Seongnam, Korea
Applied Scientist Jul. 2021 - Aug. 2024
Research Intern July. 2020 - Dec. 2020
University of Washington Seattle, WA, USA
Visiting Scholar (remote) Jan. 2021 - Jul. 2021
Mentor: Sewon Min Advisor: Hannaneh Hajishirzi, Luke Zettlemoyer
Korea University Seoul, Korea
Graduate Research Assistant (M.E.) Mar. 2019 - Aug. 2021
Advisor: Jaewoo Kang
Publications
* indicates equal contribution.Safe and Scalable Web Agent Learning via Recreated Websites
Hyungjoo Chae, Jungsoo Park, Alan Ritter
arXiv preprint
Didactic to Constructive: Turning Expert Solutions into Learnable Reasoning
Ethan Mendes, Jungsoo Park, Alan Ritter
arXiv preprint
Anticipatory Evaluation of Language Models
Jungsoo Park, Ethan Mendes, Gabriel Stanovsky, Alan Ritter
arXiv preprint
Can LLMs Help Uncover Insights about LLMs? A Large-Scale, Evolving Literature Analysis of Frontier LLMs
Jungsoo Park, Junmo Kang, Gabriel Stanovsky, Alan Ritter
Association for Computational Linguistics
Optimizing Test-Time Query Representations for Dense Retrieval
Mujeen Sung, Jungsoo Park, Jaewoo Kang, Danqi Chen, Jinhyuk Lee
Empirical Methods in Natural Language Processing-Findings
Empowering Sentence Encoders with Prompting and Label Retrieval for Zero-shot Text Classification
Jimin Hong*, Jungsoo Park*, Daeyoung Kim*, Seongjae Choi, Bokyung Son, Jaewook Kang
arXiv preprint
FaVIQ: FAct Verification from Information-seeking Questions
Jungsoo Park*, Sewon Min*, Jaewoo Kang, Luke Zettlemoyer, Hannaneh Hajishirzi
Association for Computational Linguistics
Consistency Training with Virtual Adversarial Discrete Perturbation
Jungsoo Park*, Gyuwan Kim*, Jaewoo Kang
North American Chapter of the ACL
Learn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answering
Gangwoo Kim, Hyunjae Kim, Jungsoo Park, Jaewoo Kang
Association for Computational Linguistics
Adversarial Subword Regularization for Robust Neural Machine Translation
Jungsoo Park, Mujeen Sung, Jinhyuk Lee, Jaewoo Kang
Empirical Methods in Natural Language Processing-Findings