ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CIKM, 2022)

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (NeurIPS, 2022)

Understanding Cross-Domain Few-Shot Learning: An Experimental Study. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CoRR, 2022)

Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction. - Taehyeon Kim 001; Namgyu Ho; Donggyu Kim; Se-Young Yun (CoRR, 2022)

Large Language Models Are Reasoning Teachers. - Namgyu Ho; Laura Schmid; Se-Young Yun (ACL (1), 2023)

HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning. - Yongjin Yang; Joonkee Kim; Yujin Kim; Namgyu Ho; James Thorne; Se-Young Yun (EMNLP (Findings), 2023)

Cross-Modal Retrieval Meets Inference: Improving Zero-Shot Classification with Cross-Modal Retrieval. - Seongha Eom; Namgyu Ho; Jaehoon Oh; Se-Young Yun (CoRR, 2023)

Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models. - Yujin Kim; Jaehong Yoon; Seonghyeon Ye; Sangmin Bae; Namgyu Ho; Sung Ju Hwang; Se-Young Yun (NAACL-HLT, 2024)

Block Transformer: Global-to-Local Language Modeling for Fast Inference. - Namgyu Ho; Sangmin Bae; Taehyeon Kim 001; Hyunjik Jo; Yireun Kim; Tal Schuster; Adam Fisch; James Thorne; Se-Young Yun (NeurIPS, 2024)

Self-Training Elicits Concise Reasoning in Large Language Models. - Tergel Munkhbat; Namgyu Ho; Seo Hyun Kim; Yongjin Yang; Yujin Kim; Se-Young Yun (ACL (Findings), 2025)

The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models. - Seungone Kim; Juyoung Suk; Ji Yong Cho; Shayne Longpre; Chaeeun Kim; Dongkeun Yoon; Guijin Son; Yejin Choi 001; Sheikh Shafayat; Jinheon Baek; Sue Hyun Park; Hyeonbin Hwang; et al. (NAACL (Long Papers), 2025)