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Taehyeon Kim 0001
Person information
- affiliation: Korea Advanced Institute of Science and Technology (KAIST), Graduate School of Artificial Intelligence, Seoul, South Korea
Other persons with the same name
- Taehyeon Kim (aka: Tae-Hyeon Kim) — disambiguation page
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2020 – today
- 2024
- [c7]Yongjin Yang, Taehyeon Kim, Se-Young Yun:
Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning. AAAI 2024: 16370-16378 - [c6]Euiin Yi, Taehyeon Kim, Hongseok Jeung, Du-Seong Chang, Se-Young Yun:
Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters. EMNLP 2024: 10789-10802 - [c5]Taehyeon Kim, Joonkee Kim, Gihun Lee, Se-Young Yun:
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions. ICLR 2024 - [i16]Taehyeon Kim, Donggyu Kim, Se-Young Yun:
Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labels. CoRR abs/2402.05353 (2024) - [i15]Marc Bartholet, Taehyeon Kim, Ami Beuret, Se-Young Yun, Joachim M. Buhmann:
Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization. CoRR abs/2402.06974 (2024) - [i14]Namgyu Ho, Sangmin Bae, Taehyeon Kim, Hyunjik Jo, Yireun Kim, Tal Schuster, Adam Fisch, James Thorne, Se-Young Yun:
Block Transformer: Global-to-Local Language Modeling for Fast Inference. CoRR abs/2406.02657 (2024) - [i13]Euiin Yi, Taehyeon Kim, Hongseok Jeung, Du-Seong Chang, Se-Young Yun:
Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters. CoRR abs/2406.16758 (2024) - 2023
- [i12]Taehyeon Kim, Joonkee Kim, Gihun Lee, Se-Young Yun:
Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions. CoRR abs/2311.00233 (2023) - [i11]Yongjin Yang, Taehyeon Kim, Se-Young Yun:
Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning. CoRR abs/2312.11260 (2023) - 2022
- [j1]Taehyeon Kim, Se-Young Yun
:
Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification. IEEE Access 10: 69741-69749 (2022) - [i10]Jaeyeon Ahn, Taehyeon Kim, Seyoung Yun:
Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spaces. CoRR abs/2202.00893 (2022) - [i9]Stephen Cha, Taehyeon Kim, Hayeon Lee, Se-Young Yun:
SuperNet in Neural Architecture Search: A Taxonomic Survey. CoRR abs/2204.03916 (2022) - [i8]Taehyeon Kim, Se-Young Yun:
Supernet Training for Federated Image Classification under System Heterogeneity. CoRR abs/2206.01366 (2022) - [i7]Taehyeon Kim, Heesoo Myeong, Se-Young Yun:
Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search. CoRR abs/2206.13130 (2022) - [i6]Taehyeon Kim, Namgyu Ho, Donggyu Kim, Se-Young Yun:
Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction. CoRR abs/2206.15241 (2022) - [i5]Taehyeon Kim, Shinhwan Kang, Hyeonjeong Shin, Deukryeol Yoon, Seongha Eom, Kijung Shin, Se-Young Yun:
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition. CoRR abs/2212.02059 (2022) - 2021
- [c4]Taehyeon Kim, Jaehoon Oh, Nakyil Kim, Sangwook Cho, Se-Young Yun:
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation. IJCAI 2021: 2628-2635 - [c3]Aleksandra Gruca, Federico Serva, Llorenç Lliso, Pilar Rípodas, Xavier Calbet, Pedro Herruzo, Jirí Pihrt, Rudolf Raevskiy, Petr Simánek, Matej Choma, Yang Li, Haiyu Dong, Yury Belousov, Sergey Polezhaev, Brian Pulfer, Minseok Seo, Doyi Kim, Seungheon Shin, Eunbin Kim, Sewoong Ahn, Yeji Choi, Jinyoung Park, Minseok Son, Seungju Cho, Inyoung Lee, Changick Kim, Taehyeon Kim, Shinhwan Kang, Hyeonjeong Shin, Deukryeol Yoon, Seongha Eom, Kijung Shin, Se-Young Yun, Bertrand Le Saux, Michael K. Kopp, Sepp Hochreiter, David P. Kreil:
Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts. NeurIPS (Competition and Demos) 2021: 292-313 - [c2]Taehyeon Kim, Jongwoo Ko, Sangwook Cho, Jinhwan Choi, Se-Young Yun:
FINE Samples for Learning with Noisy Labels. NeurIPS 2021: 24137-24149 - [i4]Taehyeon Kim, Jongwoo Ko, Jinhwan Choi, Sangwook Cho, Se-Young Yun:
FINE Samples for Learning with Noisy Labels. CoRR abs/2102.11628 (2021) - [i3]Taehyeon Kim, Jaehoon Oh, Nakyil Kim, Sangwook Cho, Se-Young Yun:
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation. CoRR abs/2105.08919 (2021) - 2020
- [i2]Taehyeon Kim, Sangmin Bae, Jin-Woo Lee, Seyoung Yun:
Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits. CoRR abs/2012.03270 (2020) - [i1]Taehyeon Kim, Jaeyeon Ahn, Nakyil Kim, Seyoung Yun:
Adaptive Local Bayesian Optimization Over Multiple Discrete Variables. CoRR abs/2012.03501 (2020)
2010 – 2019
- 2019
- [c1]Taehyeon Kim, Jonghyup Kim, Seyoung Yun:
Efficient Model for Image Classification With Regularization Tricks. NeurIPS (Competition and Demos) 2019: 13-26
Coauthor Index
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last updated on 2024-11-15 19:32 CET by the dblp team
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