Publications
Peer-Reviewed Papers
Brain-inspired Lp-Convolution benefits large kernels and aligns better with visual cortex
Jea Kwon, Kyungwoo Song*, C. Justin Lee*
ICLR 2024 Workshop
Bibimbap: Pre-trained models ensemble for Domain Generalization
Jinho Kang, Taero Kim, Yewon Kim, Changdae Oh, Jiyoung Jung, Rakwoo Chang, Kyungwoo Song
Pattern Recognition 2024
[paper]
Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners
Keon-Hee Park, Kyungwoo Song*, Gyeong-Moon Park*
CVPR 2024
Sentiment Analysis of Online Responses in the Performing Arts with Large Language Models
Baekryun Seong, Kyungwoo Song
Heliyon 2023
[paper]
Towards Calibrated Robust Fine-Tuning of Vision-Language Models
Changdae Oh, Mijoo Kim, Hyesu Lim, Junhyeok Park, Euiseog Jeong, Zhi-Qi Cheng, Kyungwoo Song
NeurIPS Workshop 2023
[paper]
Geodesic Multi-Modal Mixup for Robust Fine-tuning
Changdae Oh*, Junhyuk So*, Hoyoon Byun, YongTaek Lim, Minchul Shin, Jong-June Jeon, Kyungwoo Song
NeurIPS 2023
[paper]
Causally Disentangled Generative Variational AutoEncoder
SeungHwan An, Kyungwoo Song, Jong-June Jeon
ECAI 2023
[paper]
COVID-19 Infection Inference with Graph Neural Networks
Kyungwoo Song*, Hojun Park*, Junggu Lee, Arim Kim, Jaehun Jung
Scientific Reports 2023
[paper]
Robust Contrastive Learning with Dynamic Mixed Margin
Junhyuk So*, Yongtaek Lim*, Yewon Kim*, Changdae Oh, Kyungwoo Song
IEEE Access 2023
[paper]
SAAL: Sharpness-Aware Active Learning
Yoon-Yeong Kim, Youngjae Cho, JoonHo Jang, Byeonghu Na, Yeongmin Kim, Kyungwoo Song, Wanmo Kang, Il-chul Moon
ICML 2023
[paper]
Sequential Likelihood-Free Inference with Neural Proposal
Dongjun Kim , Kyungwoo Song , Yoon-Yeong Kim , Yongjin Shin , Wanmo Kang , Il-Chul Moon , Weonyoung Joo
Pattern Recognition Letters 2023
[paper]
BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning
Changdae Oh, Hyeji Hwang, Hee-young Lee, YongTaek Lim, Geunyoung Jung, Jiyoung Jung, Hosik Choi, Kyungwoo Song
CVPR 2023
Leveraging Skill-to-Skill Supervision for Knowledge Tracing
Hyeondey Kim, Yun Jegal, Jinwoo Nam, Minjae Lee, Kyungwoo Song
AAAI 2023 Workshop AI4Edu
[paper]
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation
JoonHo Jang, Byeonghu Na, DongHyeok Shin, Mingi Ji, Kyungwoo Song, Il-Chul Moon
NeurIPS 2022
[paper]
Improving Group-based Robustness and Calibration via Ordered Risk and Confidence Regularization
Seungjae Shin, Byeonghu Na, HeeSun Bae, JoonHo Jang, Hyemi Kim, Kyungwoo Song, Youngjae Cho, Il-chul Moon
ICML 2022 Workshop SCIS
[paper]
Learning Fair Representation via Distributional Contrastive Disentanglement
Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song
KDD 2022
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model
HeeSun Bae, Seungjae Shin, JoonHo Jang, Byeonghu Na, Kyungwoo Song, Il-Chul Moon
ICML 2022
[paper]
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-chul Moon
ICML 2022
[paper]
Efficient Approximate Inference for Stationary Kernel on Frequency Domain
Yohan Jung, Kyungwoo Song, Jinkyoo Park
ICML 2022
[paper]
LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning
Yooon-Yeong Kim, Kyungwoo Song, JoonHo Jang, Il-chul Moon
NeurIPS 2021
[paper]
Implicit Kernel Attention
Kyungwoo Song, Yohan Jung, Dongjun Kim, Il-Chul Moon
AAAI 2021
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder
Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo, Wanmo Kang, Il-Chul Moon.
AAAI 2021
[paper]
Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation
Seungjae Shin, Kyungwoo Song, JoonHo Jang, Hyemi Kim, Weonyoung Joo, Il-Chul Moon
Findings of EMNLP 2020
[paper]
Deep Generative Positive-Unlabeled Learning under Selection Bias
ByeongHu Na, Hyemi Kim, Kyungwoo Song, Weonyoung Joo, Yoonyeong Kim, Il-Chul Moon
CIKM 2020
[paper]
Context Aware Sequence Modeling
Kyungwoo Song
IJCAI 2020 Doctoral Consortium
[paper]
Bivariate Beta-LSTM
Kyungwoo Song, JoonHo Jang, Seungjae Shin, Il-Chul Moon
AAAI 2020
[paper] [code]
Hierarchically Clustered Representation Learning
Su-Jin Shin, Kyungwoo Song, Il-Chul Moon
AAAI 2020
[paper]
Sequential Recommendation with Relation-Aware Kernelized Self-Attention
Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoonyeong Kim, Il-Chul Moon
AAAI 2020
[paper]
Hierarchical Context enabled Recurrent Neural Network for Recommendation
Kyungwoo Song*, Mingi Ji*, Sungrae Park, Il-Chul Moon
AAAI 2019
[paper] [code]
Adversarial Dropout for Recurrent Neural Networks
Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, Il-Chul Moon
AAAI 2019
[paper] [code]
Ballistic Coefficient Estimation with Gaussian Process Particle Filter
Il-Chul Moon, Jinhyung Tak, Sang-Hyeon Kim, Kyungwoo Song
ICCAS 2018
[paper]
Neural Ideal Point Estimation Network
Kyungwoo Song, Wonsung Lee, Il-Chul Moon
AAAI 2018
[paper] [code]
State Prediction of High-speed Ballistic Vehicles with Gaussian Process
Il-Chul Moon, Kyungwoo Song, Sang-Hyeon Kim, Han-Lim Choi
International Journal of Control, Automation, and Systems (IJCAS) 2018
[paper]
Augmented Variational Autoencoders for Collaborative Filtering with Auxiliary Information
Wonsung Lee, Kyungwoo Song, Il-Chul Moon
CIKM 2017
[paper]
Data-driven ballistic coefficient learning for future state prediction of high-speed vehicles
Kyungwoo Song, Sang-Hyeon Kim, Jinhyung Tak, Han-Lim Choi, Il-Chul Moon
FUSION 2016
[paper] [slide]
Identifying the evolution of disasters and responses with network-text analysis
Kyungwoo Song, Do-Hyeong Kim, Su-Jin Shin, Il-Chul Moon
SMC 2014
[paper] [slide]
(* Equal Contribution)