Efficient Model for Image Classification With Regularization Tricks. - Taehyeon Kim 001; Jonghyup Kim; Seyoung Yun (NeurIPS (Competition and Demos), 2019)

Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits. - Taehyeon Kim 001; Sangmin Bae; Jin-Woo Lee; Seyoung Yun (CoRR, 2020)

Adaptive Local Bayesian Optimization Over Multiple Discrete Variables. - Taehyeon Kim 001; Jaeyeon Ahn; Nakyil Kim; Seyoung Yun (CoRR, 2020)

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation. - Taehyeon Kim 001; Jaehoon Oh; Nakyil Kim; Sangwook Cho; Se-Young Yun (IJCAI, 2021)

Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts. - Aleksandra Gruca; Federico Serva; Llorenç Lliso; Pilar Rípodas; Xavier Calbet; Pedro Herruzo; Jirí Pihrt; Rudolf Raevskiy; Petr Simánek; Matej Choma; Yang Li; Haiyu Dong; et al. (NeurIPS (Competition and Demos), 2021)

FINE Samples for Learning with Noisy Labels. - Taehyeon Kim 001; Jongwoo Ko; Sangwook Cho; Jinhwan Choi; Se-Young Yun (NeurIPS, 2021)

Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification. - Taehyeon Kim 001; Se-Young Yun (IEEE Access, 2022)

Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spaces. - Jaeyeon Ahn; Taehyeon Kim 001; Seyoung Yun (CoRR, 2022)

SuperNet in Neural Architecture Search: A Taxonomic Survey. - Stephen Cha; Taehyeon Kim 001; Hayeon Lee; Se-Young Yun (CoRR, 2022)

Supernet Training for Federated Image Classification under System Heterogeneity. - Taehyeon Kim 001; Se-Young Yun (CoRR, 2022)

Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search. - Taehyeon Kim 001; Heesoo Myeong; 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)

Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition. - Taehyeon Kim 001; Shinhwan Kang; Hyeonjeong Shin; Deukryeol Yoon; Seongha Eom; Kijung Shin; Se-Young Yun (CoRR, 2022)

Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions. - Taehyeon Kim 001; Joonkee Kim; Gihun Lee; Se-Young Yun (CoRR, 2023)

Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning. - Yongjin Yang; Taehyeon Kim 001; Se-Young Yun (AAAI, 2024)

Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters. - Euiin Yi; Taehyeon Kim 001; Hongseok Jeung; Du-Seong Chang; Se-Young Yun (EMNLP, 2024)

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions. - Taehyeon Kim 001; Joonkee Kim; Gihun Lee; Se-Young Yun (ICLR, 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)

Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labels. - Taehyeon Kim 001; Donggyu Kim; Se-Young Yun (CoRR, 2024)

Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization. - Marc Bartholet; Taehyeon Kim 001; Ami Beuret; Se-Young Yun; Joachim M. Buhmann (CoRR, 2024)

C2: Scalable Auto-Feedback for LLM-based Chart Generation. - Woosung Koh; Jang Han Yoon; Minhyung Lee; Youngjin Song; Jaegwan Cho; Jaehyun Kang; Taehyeon Kim 001; Se-young Yun; Youngjae Yu; Bongshin Lee (CoRR, 2024)

FLR: Label-Mixture Regularization for Federated Learning with Noisy Labels. - Taehyeon Kim 001; Donggyu Kim; Se-Young Yun (Trans. Mach. Learn. Res., 2024)

C²: Scalable Auto-Feedback for LLM-based Chart Generation. - Woosung Koh; Jang Han Yoon; Minhyung Lee; Youngjin Song; Jaegwan Cho; Jaehyun Kang; Taehyeon Kim 001; Se-Young Yun; Youngjae Yu; Bongshin Lee (NAACL (Long Papers), 2025)

Guiding Reasoning in Small Language Models with LLM Assistance. - Yujin Kim; Euiin Yi; Minu Kim; Se-Young Yun; Taehyeon Kim 001 (CoRR, 2025)

AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners. - Woosung Koh; Wonbeen Oh; Jaein Jang; Minhyung Lee; Hyeongjin Kim; Ah Yeon Kim; Joonkee Kim; Junghyun Lee; Taehyeon Kim 001; Se-Young Yun (CoRR, 2025)

LLM Agents for Bargaining with Utility-based Feedback. - Jihwan Oh; Murad Aghazada; Se-Young Yun; Taehyeon Kim 001 (CoRR, 2025)