Ph.D. Student, Georgia Tech
School of Interactive Computing
Coda 1147M
junmo.kang [AT] gatech.edu
Hello! I am currently a third-year Ph.D. student in the School of Interactive Computing at Georgia Tech advised by Alan Ritter and Wei Xu. Previously, I completed my M.S. in Computer Science at KAIST, where I started my NLP journey. I had a wonderful time interning at MIT-IBM Watson AI Lab twice.
My research focuses on developing NLP models that are efficient and robust, with the goal of ensuring their practicality in real-world scenarios.
In particular, below are some keywords of my recent interests:
MIT-IBM Watson AI Lab Cambridge, MA, USA
Research Intern May. 2024 - Aug. 2024
Research Intern May. 2023 - Aug. 2023
Host: Leonid Karlinsky, Rogerio Feris
Georgia Institute of Technology Atlanta, GA, USA
Graduate Research Assistant (Ph.D.) Aug. 2022 - Present
Advisor: Alan Ritter, Wei Xu
KAIST IR&NLP Lab Daejeon, Republic of Korea
Research Associate Mar. 2021 - July. 2022
Graduate Research Assistant (M.S.) Feb. 2019 - Feb. 2021
Advisor: Sung-Hyon Myaeng
Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts
Junmo Kang, Leonid Karlinsky, Hongyin Luo, Zhen Wang, Jacob Hansen, James Glass, David Cox, Rameswar Panda, Rogerio Feris, Alan Ritter
Preprint
Schema-Driven Information Extraction from Heterogeneous Tables
Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Mark Dredze, Alan Ritter
Preprint
Self-Specialization: Uncovering Latent Expertise within Large Language Models
Junmo Kang, Hongyin Luo, Yada Zhu, Jacob Hansen, James Glass, David Cox, Alan Ritter, Rogerio Feris, Leonid Karlinsky
ACL 2024 Findings
Why So Gullible? Enhancing the Robustness of Retrieval-Augmented Models against Counterfactual Noise
Giwon Hong*, Jeonghwan Kim*, Junmo Kang*, Sung-Hyon Myaeng, Joyce Jiyoung Whang
NAACL 2024 Findings
Distill or Annotate? Cost-Efficient Fine-Tuning of Compact Models
Junmo Kang, Wei Xu, Alan Ritter
ACL 2023
Graph-Induced Transformers for Efficient Multi-Hop Question Answering
Giwon Hong, Jeonghwan Kim, Junmo Kang, Sung-Hyon Myaeng
EMNLP 2022
Exploiting Numerical-Contextual Knowledge to Improve Numerical Reasoning in Question Answering
Jeonghwan Kim, Junmo Kang, Giwon Hong, Kyung-min Kim, Sung-Hyon Myaeng
NAACL 2022 Findings
Ultra-High Dimensional Sparse Representations with Binarization for Efficient Text Retrieval
Kyoung-Rok Jang, Junmo Kang, Giwon Hong, Sung-Hyon Myaeng, Joohee Park, Taewon Yoon, Heecheol Seo
EMNLP 2021
Leveraging Order-Free Tag Relations for Context-Aware Recommendation
Junmo Kang, Jeonghwan Kim, Suwon Shin, Sung-Hyon Myaeng
EMNLP 2021
Have You Seen That Number? Investigating Extrapolation in Question Answering Models
Jeonghwan Kim, Giwon Hong, Kyung-min Kim, Junmo Kang, Sung-Hyon Myaeng
EMNLP 2021
Can You Distinguish Truthful from Fake Reviews? User Analysis and Assistance Tool for Fake Review Detection
Jeonghwan Kim*, Junmo Kang*, Suwon Shin*, Sung-Hyon Myaeng
HCI+NLP@EACL 2021
Regularization of Distinct Strategies for Unsupervised Question Generation
Junmo Kang*, Giwon Hong*, Haritz Puerto San Roman*, Sung-Hyon Myaeng
EMNLP 2020 Findings
Handling Anomalies of Synthetic Questions in Unsupervised Question Answering
Giwon Hong*, Junmo Kang*, Doyeon Lim*, Sung-Hyon Myaeng
COLING 2020
Let Me Know What to Ask: Interrogative-Word-Aware Question Generation
Junmo Kang*, Haritz Puerto San Roman*, Sung-Hyon Myaeng
MRQA@EMNLP 2019
Full CV in PDF.