Papers
2024
[37] Wonwoo Cho*, Dongmin Choi*, Hyesu Lim*, Jinho Choi, Saemee Choi, Hyun-seok Min, Sungbin Lim, Jaegul Choo, "Slice and Conquer: A Planar-to-3D Framework for Efficient Interactive Segmentation of Volumetric Images", WACV 2024 (*: equal contributions).
2023
[36] Gunsoo Han, Daejin Jo, Daniel Wontae Nam, Eunseop Yoon, Taehwan Kwon, Seungeun Rho, Kyoung-Woon On, Chang D. Yoo, Sungwoong Kim, "Efficient Latent Variable Modeling for Knowledge-Grounded Dialogue Generation", The Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023 (Long, Findings).
[35] Sungbin Lim*, Eunbi Yoon, Taehyun Byun, Taewon Kang, Seungwoo Kim, Kyungjae Lee, Sungjoon Choi*, "Score-based Generative Modeling through Stochastic Evolution Equations in Hilbert Spaces", Neural Information Processing Systems (NeurIPS) 2023 (spotlight).
[34] Eunbi Yoon, Keehun Park, Sungwoong Kim, Sungbin Lim, "Score-based Generative Models with Levy Processes", Neural Information Processing Systems (NeurIPS) 2023 (spotlight).
[33] Jaeyoung Kim, Dongbin Na, Sungchul Choi, Sungbin Lim*, "Bag of Tricks for In-Distribution Calibration of Pretrained Transformers", EACL 2023 (findings).
[32] Aigerim Bogyrbayeva, Taehyun Yoon, Hanbum Ko, Sungbin Lim, Hyokun Yun, Changhyun Kwon*, "A deep reinforcement learning approach for solving the Traveling Salesman Problem with Drone", Transportation Research Part C: Emerging Technologies, 2023
[31] Sungwoong Kim*, Daejin Jo*, Donghoon Lee*, and Jongmin Kim*, "MAGVLT: Masked Generative Vision-and-Language Transformer", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2023 (*: equal contributions).
[30] Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, and Bjoern Menze, "The Liver Tumor Segmentation Benchmark (LiTS)", Medical Image Analysis, vol. 84, Feb., 2023.
2022
[29] Daejin Jo*, Sungwoong Kim*, Daniel Wontae Nam*, Taehwan Kwon, Seungeun Rho, Jongmin Kim, and Donghoon Lee, "LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward", Neural Information Processing Systems (NeurIPS) 2022 (*: equal contributions).
[28] Daejin Jo, Taehwan Kwon, Eun-Sol Kim, and Sungwoong Kim, "Selective Token Generation for Few-shot Natural Language Generation", International Conference on Computational Linguistics (COLING) 2022 (oral).
[27] Eric Hambro, Sharada Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, Daejin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Kuttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktaschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, and Michal Sypetkowski, "Insights From the NeurIPS 2021 NetHack Challenge", arXiv:2203.11889, 2022.
[26] Doyup Lee, Sungwoong Kim, Ildoo Kim, Yeongjae Cheon, Minsu Cho, and Wook-Shin Han, "Contrastive Regularization for Semi-Supervised Learning", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) L3D-IVU Workshop, 2022.
2021
[25] Chiheon Kim, Saehoon Kim, Jongmin Kim, Donghoon Lee, and Sungwoong Kim, "Automated Learning Rate Scheduler for Large-batch Training", International Conference on Machine Learning (ICML) AutoML Workshop, 2021.
[24] Saehoon Kim, Sungwoong Kim, and Juho Lee, "Hybrid Generative-Contrastive Representation Learning", arXiv:2106.06162, 2021.
[23] Byungseok Roh, Wuhyun Shin, Ildoo Kim, and Sungwoong Kim, "Spatially Consistent Representation Learning", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[22] Taesup Kim, Sungwoong Kim, and Yoshua Bengio, "Visual Concept Reasoning Networks", AAAI Conference on Artificial Intelligence (AAAI), 2021.
2020
[21] Ildoo Kim, Younghoon Kim, and Sungwoong Kim, "Learning Loss for Test-Time Augmentation", Neural Information Processing Systems (NeurIPS), 2020.
[20] Woonhyuk Baek, Ildoo Kim, Sungwoong Kim, and Sungbin Lim, "AutoCLINT: The Winning Method in AutoCV Challenge 2019", arXiv:2005.04373, 2020.
[19] Chiheon Kim, Heungsub Lee, Myungryong Jeong, Woonhyuk Baek, Boogeon Yoon, Ildoo Kim, Sungbin Lim, and Sungwoong Kim, "torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models", arXiv:2004.09910, 2020.
[18] Ildoo Kim, Woonhyuk Bae, and Sungwoong Kim, "Spatially Attentive Output Layer for Image Classification", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
2019
[17] Sangwoo Mo, Chiheon Kim, Sungwoong Kim, Minsu Cho, and Jinwoo Shin, "Mining GOLD Samples for Conditional GANs", Neural Information Processing Systems (NeurIPS), 2019.
[16] Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, and Sungwoong Kim, "Fast autoaugment", Neural Information Processing Systems (NeurIPS), 2019.
[15] Sungwoong Kim, Ildoo Kim, Sungbin Lim, Woonhyuk Baek, Chiheon Kim, Hyungjoo Cho, Boogeon Yoon, and Taesup Kim, "Scalable Neural Architecture Search for 3D Medical Image Segmentation", International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.
[14] Jongmin Kim, Taesup Kim, Sungwoong Kim, and Chang D Yoo, "Edge-Labeling Graph Neural Network for Few-shot Learning", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, June. 2019.
2018
[13] Taesup Kim, Jaesik Yoon, Ousmane Dia, Sungwoong Kim, Yoshua Bengio, and Sungjin Ahn, "Bayesian Model-Agnostic Meta-Learning", Neural Information Processing Systems (NeurIPS), 2018.
~ 2017
[12] Jorg H. Kappes, Bjoern Andres, Fred A. Hamprecht, Christoph Schnorr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Thorben Kroger, Jan Lellmann, Nikos Komodakis, Bogdan Savchynskyy, and Carsten Rother, "A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems", International Journal of Computer Vision, vol. 115, no. 2, pp. 155-184, Nov., 2015.
[11] Sungwoong Kim, Chang D. Yoo, Sebastian Nowozin, and Pushmeet Kohli, "Image Segmentation Using Higher-Order Correlation Clustering", IEEE Transaction on Pattern Analysis and Machine Intelligence, vol.36, no.9, pp.1761-1774, September 2014.
[10] Jorg H. Kappes, Bjoern Andres, Fred A. Hamprecht, Christoph Schnorr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Jan Lellmann, Nikos Komodakis, and Carsten Rother, "A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June. 2013.
[9] Sungwoong Kim, Sebastian Nowozin, Pushmeet Kohli, and Chang D. Yoo, "Task-Specific Image Partitioning", IEEE Transaction on Image Processing, vol. 22, no. 2, pp. 488-500, Feb., 2013.
[8] Sungwoong Kim, Sebastian Nowozin, Pushmeet Kohli, and Chang D. Yoo, "Higher-Order Correlation Clustering for Image Segmentation", Neural Information Processing Systems (NIPS), Granada, Spain, Dec. 2011.
[7] Sungwoong Kim, Sungrack Yun, and Chang D. Yoo, "Large Margin Discriminative Semi-Markov Model for Phonetic Recognition", IEEE Transaction on Audio, Speech, and Language Processing, vol.19, no.7, pp.1999-2012, September 2011.
[6] Sungwoong Kim, Jongmin Kim, Sungrack Yun, and Chang D. Yoo, "$\nu$-Structured Support Vector Machines", IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Kittila, Finland, pp. 450--455, Aug. 2010.
[5] O. Thomas, P. Sunehag, G. Dror, Sungrack Yun, Sungwoong Kim, M. Robards, A. Smola, D. Greene, and P. Saunders, "Wearable-Sensor Activity Analysis Using Semi-Markov Models with a Grammar", Pervasive and Mobile Computing, vol. 6, no. 3, pp. 342--350, June 2010.
[4] Sungwoong Kim, Sungrack Yun, and Chang D. Yoo, "Large Margin Training of Semi-Markov Model for Phonetic Recognition", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Dallas, USA, pp. 1910--1913, Mar. 2010.
[3] Dalwon Jang, Chang D. Yoo, Sunil Lee, Sungwoong Kim, and Ton Kalker, "Pairwise Boosted Audio Fingerprint", IEEE Trans. Information Forensics and Security, vol.4, no.4, pp.995-1004, December 2009.
[2] Sungwoong Kim, Sungrack Yun, and Chang D. Yoo, "Margin-Enhanced Maximum Mutual Information Estimation for Hidden Markov Models", IEEE International Symposium on Industrial Electronics (ISIE), Seoul, Korea, pp. 1347--1351, July 2009.
[1] Sungwoong Kim, and Chang D. Yoo, "Boosted Binary Audio Fingerprint Based on Spectral Subband Moments", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, USA, pp. 241--244, April 2007.