b'Jung-Woo Ha'

research

∙ 07/27/2022

Generator Knows What Discriminator Should Learn in Unconditional GANs

Recent methods for conditional image generation benefit from dense super...

Gayoung Lee, et al. ∙

research

∙ 07/19/2022

Time Is MattEr: Temporal Self-supervision for Video Transformers

Understanding temporal dynamics of video is an essential aspect of learn...

Sukmin Yun, et al. ∙

research

∙ 06/29/2022

Deformable Graph Transformer

Transformer-based models have been widely used and achieved state-of-the...

Jinyoung Park, et al. ∙

research

∙ 06/17/2022

Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images

Evaluation metrics in image synthesis play a key role to measure perform...

Jiyeon Han, et al. ∙

research

∙ 05/30/2022

Dataset Condensation via Efficient Synthetic-Data Parameterization

The great success of machine learning with massive amounts of data comes...

Jang-Hyun Kim, et al. ∙

research

∙ 05/19/2022

Two-Step Question Retrieval for Open-Domain QA

The retriever-reader pipeline has shown promising performance in open-do...

Yeon Seonwoo, et al. ∙

research

∙ 04/28/2022

On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model

Many recent studies on large-scale language models have reported success...

Seongjin Shin, et al. ∙

research

∙ 03/29/2022

Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries

Learning under a continuously changing data distribution with incorrect ...

Jihwan Bang, et al. ∙

research

∙ 03/26/2022

Metropolis-Hastings Data Augmentation for Graph Neural Networks

Graph Neural Networks (GNNs) often suffer from weak-generalization due t...

Hyeonjin Park, et al. ∙

research

∙ 02/21/2022

Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks

In the deep learning era, long video generation of high-quality still re...

Sihyun Yu, et al. ∙

research

∙ 12/30/2021

Contrastive Fine-grained Class Clustering via Generative Adversarial Networks

Unsupervised fine-grained class clustering is practical yet challenging ...

Yunji Kim, et al. ∙

research

∙ 10/19/2021

Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference

Despite rapid advances in continual learning, a large body of research i...

Hyunseo Koh, et al. ∙

research

∙ 09/10/2021

What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers

GPT-3 shows remarkable in-context learning ability of large-scale langua...

Boseop Kim, et al. ∙

research

∙ 06/18/2021

Weakly Supervised Pre-Training for Multi-Hop Retriever

In multi-hop QA, answering complex questions entails iterative document ...

Yeon Seonwoo, et al. ∙

research

∙ 05/20/2021

KLUE: Korean Language Understanding Evaluation

We introduce Korean Language Understanding Evaluation (KLUE) benchmark. ...

Sungjoon Park, et al. ∙

research

∙ 04/15/2021

Reward Optimization for Neural Machine Translation with Learned Metrics

Neural machine translation (NMT) models are conventionally trained with ...

Raphael Shu, et al. ∙

research

∙ 03/31/2021

Rainbow Memory: Continual Learning with a Memory of Diverse Samples

Continual learning is a realistic learning scenario for AI models. Preva...

Jihwan Bang, et al. ∙

research

∙ 03/01/2021

Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning

In recent years, graph neural networks (GNNs) have been widely adopted i...

Dasol Hwang, et al. ∙

research

∙ 01/31/2021

M2FN: Multi-step Modality Fusion for Advertisement Image Assessment

Assessing advertisements, specifically on the basis of user preferences ...

Kyung-Wha Park, et al. ∙

research

∙ 12/03/2020

DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances

Recent advances in pre-trained language models have significantly improv...

Xiaodong Gu, et al. ∙

research

∙ 11/05/2020

Context-Aware Answer Extraction in Question Answering

Extractive QA models have shown very promising performance in predicting...

Yeon Seonwoo, et al. ∙

research

∙ 10/23/2020

ST-BERT: Cross-modal Language Model Pre-training For End-to-end Spoken Language Understanding

Language model pre-training has shown promising results in various downs...

Minjeong Kim, et al. ∙

research

∙ 08/14/2020

Which Strategies Matter for Noisy Label Classification? Insight into Loss and Uncertainty

Label noise is a critical factor that degrades the generalization perfor...

Wonyoung Shin, et al. ∙

research

∙ 07/16/2020

Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs

Graph neural networks have shown superior performance in a wide range of...

Dasol Hwang, et al. ∙

research

∙ 07/06/2020

CareCall: a Call-Based Active Monitoring Dialog Agent for Managing COVID-19 Pandemic

Tracking suspected cases of COVID-19 is crucial to suppressing the sprea...

Sang-Woo Lee, et al. ∙

research

∙ 06/19/2020

Efficient Active Learning for Automatic Speech Recognition via Augmented Consistency Regularization

The cost of labeling transcriptions for large speech corpora becomes a b...

Jihwan Bang, et al. ∙

research

∙ 06/15/2020

Slowing Down the Weight Norm Increase in Momentum-based Optimizers

Normalization techniques, such as batch normalization (BN), have led to ...

Byeongho Heo, et al. ∙

research

∙ 05/18/2020

Graphs, Entities, and Step Mixture

Existing approaches for graph neural networks commonly suffer from the o...

Kyuyong Shin, et al. ∙

research

∙ 04/20/2020

ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers

Automatic speech recognition (ASR) via call is essential for various app...

Jung-Woo Ha, et al. ∙

research

∙ 02/10/2020

Modeling Musical Onset Probabilities via Neural Distribution Learning

Musical onset detection can be formulated as a time-to-event (TTE) or ti...

Jaesung Huh, et al. ∙

research

∙ 12/04/2019

StarGAN v2: Diverse Image Synthesis for Multiple Domains

A good image-to-image translation model should learn a mapping between d...

Yunjey Choi, et al. ∙

research

∙ 10/15/2019

Neural Approximation of an Auto-Regressive Process through Confidence Guided Sampling

We propose a generic confidence-based approximation that can be plugged ...

YoungJoon Yoo, et al. ∙

research

∙ 10/06/2019

Which Ads to Show? Advertisement Image Assessment with Auxiliary Information via Multi-step Modality Fusion

Assessing aesthetic preference is a fundamental task related to human co...

Kyung-Wha Park, et al. ∙

research

∙ 07/24/2019

Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation

Graph Neural Networks (GNNs) have been emerging as a promising method fo...

Kyung-Min Kim, et al. ∙

research

∙ 03/23/2019

Photorealistic Style Transfer via Wavelet Transforms

Recent style transfer models have provided promising artistic results. H...

Jaejun Yoo, et al. ∙

research

∙ 03/07/2019

Phase-aware Speech Enhancement with Deep Complex U-Net

Most deep learning-based models for speech enhancement have mainly focus...

Hyeong-Seok Choi, et al. ∙

research

∙ 02/22/2019

Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation

Answerer in Questioner's Mind (AQM) is an information-theoretic framewor...

Sang-Woo Lee, et al. ∙

research

∙ 12/21/2018

Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement

We present a hybrid framework that leverages the trade-off between tempo...

Jang-Hyun Kim, et al. ∙

research

∙ 10/08/2018

CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms

Many hyperparameter optimization (HyperOpt) methods assume restricted co...

Jinwoong Kim, et al. ∙

research

∙ 10/08/2018

NSML: Meet the MLaaS platform with a real-world case study

The boom of deep learning induced many industries and academies to intro...

Hanjoo Kim, et al. ∙

research

∙ 01/17/2018

Reinforcement Learning based Recommender System using Biclustering Technique

A recommender system aims to recommend items that a user is interested i...

Sungwoon Choi, et al. ∙

research

∙ 12/16/2017

NSML: A Machine Learning Platform That Enables You to Focus on Your Models

Machine learning libraries such as TensorFlow and PyTorch simplify model...

Nako Sung, et al. ∙

research

∙ 12/16/2017

Automatic Music Highlight Extraction using Convolutional Recurrent Attention Networks

Music highlights are valuable contents for music services. Most methods ...

Jung-Woo Ha, et al. ∙

research

∙ 11/30/2017

Highrisk Prediction from Electronic Medical Records via Deep Attention Networks

Predicting highrisk vascular diseases is a significant issue in the medi...

You Jin Kim, et al. ∙

research

∙ 11/24/2017

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Recent studies have shown remarkable success in image-to-image translati...

Yunjey Choi, et al. ∙

research

∙ 10/18/2017

Representation Learning of Music Using Artist Labels

Recently, feature representation by learning algorithms has drawn great ...

Jiyoung Park, et al. ∙

research

∙ 06/28/2017

Energy-Based Sequence GANs for Recommendation and Their Connection to Imitation Learning

Recommender systems aim to find an accurate and efficient mapping from h...

Jaeyoon Yoo, et al. ∙

research

∙ 11/02/2016

Dual Attention Networks for Multimodal Reasoning and Matching

We propose Dual Attention Networks (DANs) which jointly leverage visual ...

Hyeonseob Nam, et al. ∙

research

∙ 10/14/2016

Hadamard Product for Low-rank Bilinear Pooling

Bilinear models provide rich representations compared with linear models...

Jin-Hwa Kim, et al. ∙

research

∙ 06/05/2016

Multimodal Residual Learning for Visual QA

Deep neural networks continue to advance the state-of-the-art of image r...

Jin-Hwa Kim, et al. ∙

Jung-Woo Ha

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