Kim, Taehyeon

15 publications

NeurIPS 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, Se-Young Yun

ICLR 2025 MMR: A Large-Scale Benchmark Dataset for Multi-Target and Multi-Granularity Reasoning Segmentation Donggon Jang, Yucheol Cho, Suin Lee, Taehyeon Kim, Daeshik Kim

NeurIPS 2024 Accelerating Blockwise Parallel Language Models with Draft Refinement Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael Riley, Sanjiv Kumar, Adrian Benton

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

ICMLW 2024 Exploring and Improving Drafts in Blockwise Parallel Decoding Taehyeon Kim, Ananda Theertha Suresh, Kishore A Papineni, Michael Riley, Sanjiv Kumar, Adrian Benton

TMLR 2024 FLR: Label-Mixture Regularization for Federated Learning with Noisy Labels Taehyeon Kim, Donggyu Kim, Se-Young Yun

ICLR 2024 Instructive Decoding: Instruction-Tuned Large Language Models Are Self-Refiner from Noisy Instructions Taehyeon Kim, Joonkee Kim, Gihun Lee, Se-Young Yun

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

NeurIPSW 2023 Distort, Distract, Decode: Instruction-Tuned Model Can Refine Its Response from Noisy Instructions Taehyeon Kim, Joonkee Kim, Gihun Lee, Se-Young Yun

NeurIPS 2023 Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection Taehyeon Kim, Eric Lin, Junu Lee, Christian Lau, Vaikkunth Mugunthan

NeurIPSW 2022 Layover Intermediate Layer for Multi-Label Classification in Efficient Transfer Learning Seongha Eom, Taehyeon Kim, Se-Young Yun

NeurIPSW 2022 Revisiting the Activation Function for Federated Image Classification Jaewoo Shin, Taehyeon Kim, Se-Young Yun

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

NeurIPS 2021 FINE Samples for Learning with Noisy Labels Taehyeon Kim, Jongwoo Ko, Sangwook Cho, JinHwan Choi, Se-Young Yun

ICCVW 2019 Tensor Train Decomposition for Efficient Memory Saving in Perceptual Feature-Maps Taehyeon Kim, Jieun Lee, Yoonsik Choe