Let Me Know What to Ask: Interrogative-Word-Aware Question Generation. - Junmo Kang; Haritz Puerto San Roman; Sung-Hyon Myaeng (MRQA@EMNLP, 2019)

Handling Anomalies of Synthetic Questions in Unsupervised Question Answering. - Giwon Hong; Junmo Kang; Doyeon Lim; Sung-Hyon Myaeng (COLING, 2020)

Regularization of Distinct Strategies for Unsupervised Question Generation. - Junmo Kang; Giwon Hong; Haritz Puerto San Roman; Sung-Hyon Myaeng (EMNLP (Findings), 2020)

A Sequence-Oblivious Generation Method for Context-Aware Hashtag Recommendation. - Junmo Kang; Jeonghwan Kim; Suwon Shin; Sung-Hyon Myaeng (CoRR, 2020)

Ultra-High Dimensional Sparse Representations with Binarization for Efficient Text Retrieval. - Kyoungrok Jang; Junmo Kang; Giwon Hong; Sung-Hyon Myaeng; Joohee Park; Taewon Yoon; Hee-Cheol Seo (EMNLP (1), 2021)

Leveraging Order-Free Tag Relations for Context-Aware Recommendation. - Junmo Kang; Jeonghwan Kim; Suwon Shin; Sung-Hyon Myaeng (EMNLP (1), 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 (1), 2021)

UHD-BERT: Bucketed Ultra-High Dimensional Sparse Representations for Full Ranking. - Kyoungrok Jang; Junmo Kang; Giwon Hong; Sung-Hyon Myaeng; Joohee Park; Taewon Yoon; Hee-Cheol Seo (CoRR, 2021)

Maximizing Efficiency of Language Model Pre-training for Learning Representation. - Junmo Kang; Suwon Shin; Jeonghwan Kim; Jae-young Jo; Sung-Hyon Myaeng (CoRR, 2021)

Graph-Induced Transformers for Efficient Multi-Hop Question Answering. - Giwon Hong; Jeonghwan Kim; Junmo Kang; Sung-Hyon Myaeng (EMNLP, 2022)

Holistic approaches to memory solutions for the Autonomous Driving Era. - Daeyong Shim; Chunseok Jeong; Euncheol Lee; Junmo Kang; Seokcheol Yoon; Yongkee Kwon; Il Park 001; Hyun Ahn; Seonyong Cha; Jinkook Kim (ISCAS, 2022)

Exploiting Numerical-Contextual Knowledge to Improve Numerical Reasoning in Question Answering. - Jeonghwan Kim; Junmo Kang; Kyung-Min Kim; Giwon Hong; Sung-Hyon Myaeng (NAACL-HLT (Findings), 2022)

Distill or Annotate? Cost-Efficient Fine-Tuning of Compact Models. - Junmo Kang; Wei Xu 004; Alan Ritter (ACL (1), 2023)

Discern and Answer: Mitigating the Impact of Misinformation in Retrieval-Augmented Models with Discriminators. - Giwon Hong; Jeonghwan Kim; Junmo Kang; Sung-Hyon Myaeng; Joyce Jiyoung Whang (CoRR, 2023)

Schema-Driven Information Extraction from Heterogeneous Tables. - Fan Bai 006; Junmo Kang; Gabriel Stanovsky; Dayne Freitag; Alan Ritter (CoRR, 2023)

Self-Specialization: Uncovering Latent Expertise within Large Language Models. - Junmo Kang; Hongyin Luo; Yada Zhu; James R. Glass; David D. Cox; Alan Ritter; Rogério Feris; Leonid Karlinsky (CoRR, 2023)

Self-Specialization: Uncovering Latent Expertise within Large Language Models. - Junmo Kang; Hongyin Luo; Yada Zhu; Jacob A. Hansen; James R. Glass; David D. Cox; Alan Ritter; Rogério Feris; Leonid Karlinsky (ACL (Findings), 2024)

Schema-Driven Information Extraction from Heterogeneous Tables. - Fan Bai 006; Junmo Kang; Gabriel Stanovsky; Dayne Freitag; Mark Dredze; Alan Ritter (EMNLP (Findings), 2024)

MATE: Meet At The Embedding - Connecting Images with Long Texts. - Young Kyun Jang; Junmo Kang; Yong Jae Lee; Donghyun Kim (EMNLP (Findings), 2024)

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-HLT (Findings), 2024)

CROSSNEWS: A Cross-Genre Authorship Verification and Attribution Benchmark. - Marcus Ma; Duong Minh Le; Junmo Kang; Yao Dou; John Cadigan; Dayne Freitag; Alan Ritter; Wei Xu 004 (AAAI, 2025)

Can LLMs Help Uncover Insights about LLMs? A Large-Scale, Evolving Literature Analysis of Frontier LLMs. - Jungsoo Park; Junmo Kang; Gabriel Stanovsky; Alan Ritter (ACL (1), 2025)

Balancing the Budget: Understanding Trade-offs Between Supervised and Preference-Based Finetuning. - Mohit Raghavendra; Junmo Kang; Alan Ritter (ACL (1), 2025)

Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts. - Junmo Kang; Leonid Karlinsky; Hongyin Luo; Zhen Wang 041; Jacob A. Hansen; James R. Glass; David Daniel Cox; Rameswar Panda; Rogério Feris; Alan Ritter (ICLR, 2025)

Seeing the Forest for the Trees: A Large Scale, Continuously Updating Meta-Analysis of Frontier LLMs. - Jungsoo Park; Junmo Kang; Gabriel Stanovsky; Alan Ritter (CoRR, 2025)

Instructify: Demystifying Metadata to Visual Instruction Tuning Data Conversion. - Jacob A. Hansen; Wei Lin 019; Junmo Kang; Muhammad Jehanzeb Mirza; Hongyin Luo; Rogério Feris; Alan Ritter; James R. Glass; Leonid Karlinsky (CoRR, 2025)