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Sangmin Bae
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2020 – today
- 2024
- [c13]Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim:
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. ACL (1) 2024: 8252-8271 - [c12]June-Woo Kim, Sangmin Bae, Won-Yang Cho, Byungjo Lee, Ho-Young Jung:
Stethoscope-Guided Supervised Contrastive Learning for Cross-Domain Adaptation on Respiratory Sound Classification. ICASSP 2024: 1431-1435 - [c11]Yujin Kim, Jaehong Yoon, Seonghyeon Ye, Sangmin Bae, Namgyu Ho, Sung Ju Hwang, Se-Young Yun:
Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models. NAACL-HLT 2024: 5401-5415 - [i17]June-Woo Kim, Miika Toikkanen, Sangmin Bae, Minseok Kim, Ho-Young Jung:
RepAugment: Input-Agnostic Representation-Level Augmentation for Respiratory Sound Classification. CoRR abs/2405.02996 (2024) - [i16]Felix den Breejen, Sangmin Bae, Stephen Cha, Se-Young Yun:
Why In-Context Learning Transformers are Tabular Data Classifiers. CoRR abs/2405.13396 (2024) - [i15]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) - [i14]Sungnyun Kim, Kangwook Jang, Sangmin Bae, Hoirin Kim, Se-Young Yun:
Learning Video Temporal Dynamics with Cross-Modal Attention for Robust Audio-Visual Speech Recognition. CoRR abs/2407.03563 (2024) - [i13]Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim:
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. CoRR abs/2407.14733 (2024) - [i12]Sihyeon Kim, Boryeong Cho, Sangmin Bae, Sumyeong Ahn, Se-Young Yun:
VACoDe: Visual Augmented Contrastive Decoding. CoRR abs/2408.05337 (2024) - 2023
- [c10]Sangmin Bae, Sungnyun Kim, Jongwoo Ko, Gihun Lee, Seungjong Noh, Se-Young Yun:
Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network. AAAI 2023: 197-205 - [c9]Sangmook Kim, Sangmin Bae, Hwanjun Song, Se-Young Yun:
Re-Thinking Federated Active Learning Based on Inter-Class Diversity. CVPR 2023: 3944-3953 - [c8]Sungnyun Kim, Sangmin Bae, Se-Young Yun:
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning. CVPR 2023: 7537-7547 - [c7]Sangmin Bae, Jongwoo Ko, Hwanjun Song, Se-Young Yun:
Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding. EMNLP 2023: 5910-5924 - [c6]Sangmin Bae, June-Woo Kim, Won-Yang Cho, Hyerim Baek, Soyoun Son, Byungjo Lee, Changwan Ha, Kyongpil Tae, Sungnyun Kim, Se-Young Yun:
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification. INTERSPEECH 2023: 5436-5440 - [i11]Sungnyun Kim, Sangmin Bae, Se-Young Yun:
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning. CoRR abs/2303.11101 (2023) - [i10]Sangmook Kim, Sangmin Bae, Hwanjun Song, Se-Young Yun:
Re-thinking Federated Active Learning based on Inter-class Diversity. CoRR abs/2303.12317 (2023) - [i9]Sangmin Bae, June-Woo Kim, Won-Yang Cho, Hyerim Baek, Soyoun Son, Byungjo Lee, Changwan Ha, Kyongpil Tae, Sungnyun Kim, Se-Young Yun:
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification. CoRR abs/2305.14032 (2023) - [i8]Sangmin Bae, Jongwoo Ko, Hwanjun Song, Se-Young Yun:
Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding. CoRR abs/2310.05424 (2023) - [i7]June-Woo Kim, Chihyeon Yoon, Miika Toikkanen, Sangmin Bae, Ho-Young Jung:
Adversarial Fine-tuning using Generated Respiratory Sound to Address Class Imbalance. CoRR abs/2311.06480 (2023) - [i6]Felix den Breejen, Sangmin Bae, Stephen Cha, Tae-Young Kim, Seounghyun Koh, Se-Young Yun:
Fine-Tuning the Retrieval Mechanism for Tabular Deep Learning. CoRR abs/2311.07343 (2023) - [i5]June-Woo Kim, Sangmin Bae, Won-Yang Cho, Byungjo Lee, Ho-Young Jung:
Stethoscope-guided Supervised Contrastive Learning for Cross-domain Adaptation on Respiratory Sound Classification. CoRR abs/2312.09603 (2023) - 2022
- [c5]Gihun Lee, Minchan Jeong, Yongjin Shin, Sangmin Bae, Se-Young Yun:
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning. NeurIPS 2022 - 2021
- [i4]Sangmin Bae, Sungnyun Kim, Jongwoo Ko, Gihun Lee, Seungjong Noh, Se-Young Yun:
Self-Contrastive Learning. CoRR abs/2106.15499 (2021) - 2020
- [c4]Gihun Lee, Sangmin Bae, Jaehoon Oh, Se-Young Yun
:
SIPA: A Simple Framework for Efficient Networks. ICDM (Workshops) 2020: 729-736 - [i3]Gihun Lee, Sangmin Bae, Jaehoon Oh, Se-Young Yun:
SIPA: A Simple Framework for Efficient Networks. CoRR abs/2004.14476 (2020) - [i2]Sungnyun Kim, Gihun Lee, Sangmin Bae, Se-Young Yun:
MixCo: Mix-up Contrastive Learning for Visual Representation. CoRR abs/2010.06300 (2020) - [i1]Taehyeon Kim, Sangmin Bae, Jin-Woo Lee, Seyoung Yun:
Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits. CoRR abs/2012.03270 (2020)
2010 – 2019
- 2019
- [c3]Yohan Joo, Jongpil Jeong, Sangmin Bae:
Under Sampling Bagging Shapelet Transformation for Hydraulic System. COINS 2019: 13-18 - [c2]Su-Hwan Jang, Jo Guejong, Jongpil Jeong
Fog Computing Architecture Based Blockchain for Industrial IoT. ICCS (3) 2019: 593-606
2000 – 2009
- 2002
- [c1]Sangmin Bae, DongSup Song, Jihye Kim, Sungho Kang:
An Efficient On-Line Monitoring BIST for Remote Service System. AISA 2002: 205-214
Coauthor Index
aka: Seyoung Yun
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last updated on 2024-09-26 01:55 CEST by the dblp team
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