Jung-Woo Ha

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NAVER Corp. ∙ Seoul National University

- Executive Officer, NAVER Corp.

- Head, NAVER AI Lab

- Head, NAVER CLOVA Research

- Co-director, SNU-NAVER Hyperscale AI Center

- Co-director, KAIST-NAVER Hypercreative AI Center

- Co-chair, AI Future Forum

- Advisory member, the Public Data Strategy Committee, Prime Minister, Korea Government.

Weakly Supervised Pre-Training for Multi-Hop Retriever

In multi-hop QA, answering complex questions entails iterative document ...
06/18/2021 ∙ by Yeon Seonwoo, et al. ∙ 8 ∙ share

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KLUE: Korean Language Understanding Evaluation

We introduce Korean Language Understanding Evaluation (KLUE) benchmark. ...
05/20/2021 ∙ by Sungjoon Park, et al. ∙ 20 ∙ share

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Reward Optimization for Neural Machine Translation with Learned Metrics

Neural machine translation (NMT) models are conventionally trained with ...
04/15/2021 ∙ by Raphael Shu, et al. ∙ 0 ∙ share

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Rainbow Memory: Continual Learning with a Memory of Diverse Samples

Continual learning is a realistic learning scenario for AI models. Preva...
03/31/2021 ∙ by Jihwan Bang, et al. ∙ 27 ∙ share

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

In recent years, graph neural networks (GNNs) have been widely adopted i...
03/01/2021 ∙ by Dasol Hwang, et al. ∙ 0 ∙ share

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M2FN: Multi-step Modality Fusion for Advertisement Image Assessment

Assessing advertisements, specifically on the basis of user preferences ...
01/31/2021 ∙ by Kyung-Wha Park, et al. ∙ 0 ∙ share

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

Recent advances in pre-trained language models have significantly improv...
12/03/2020 ∙ by Xiaodong Gu, et al. ∙ 0 ∙ share

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Context-Aware Answer Extraction in Question Answering

Extractive QA models have shown very promising performance in predicting...
11/05/2020 ∙ by Yeon Seonwoo, et al. ∙ 7 ∙ share

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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...
10/23/2020 ∙ by Minjeong Kim, et al. ∙ 0 ∙ share

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

Label noise is a critical factor that degrades the generalization perfor...
08/14/2020 ∙ by Wonyoung Shin, et al. ∙ 6 ∙ share

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

Graph neural networks have shown superior performance in a wide range of...
07/16/2020 ∙ by Dasol Hwang, et al. ∙ 26 ∙ share

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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...
07/06/2020 ∙ by Sang-Woo Lee, et al. ∙ 13 ∙ share

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Efficient Active Learning for Automatic Speech Recognition via Augmented Consistency Regularization

The cost of labeling transcriptions for large speech corpora becomes a b...
06/19/2020 ∙ by Jihwan Bang, et al. ∙ 0 ∙ share

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Slowing Down the Weight Norm Increase in Momentum-based Optimizers

Normalization techniques, such as batch normalization (BN), have led to ...
06/15/2020 ∙ by Byeongho Heo, et al. ∙ 16 ∙ share

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Graphs, Entities, and Step Mixture

Existing approaches for graph neural networks commonly suffer from the o...
05/18/2020 ∙ by Kyuyong Shin, et al. ∙ 16 ∙ share

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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...
04/20/2020 ∙ by Jung-Woo Ha, et al. ∙ 2 ∙ share

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Modeling Musical Onset Probabilities via Neural Distribution Learning

Musical onset detection can be formulated as a time-to-event (TTE) or ti...
02/10/2020 ∙ by Jaesung Huh, et al. ∙ 0 ∙ share

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StarGAN v2: Diverse Image Synthesis for Multiple Domains

A good image-to-image translation model should learn a mapping between d...
12/04/2019 ∙ by Yunjey Choi, et al. ∙ 22 ∙ share

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

We propose a generic confidence-based approximation that can be plugged ...
10/15/2019 ∙ by YoungJoon Yoo, et al. ∙ 16 ∙ share

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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...
10/06/2019 ∙ by Kyung-Wha Park, et al. ∙ 0 ∙ share

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Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation

Graph Neural Networks (GNNs) have been emerging as a promising method fo...
07/24/2019 ∙ by Kyung-Min Kim, et al. ∙ 0 ∙ share

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Photorealistic Style Transfer via Wavelet Transforms

Recent style transfer models have provided promising artistic results. H...
03/23/2019 ∙ by Jaejun Yoo, et al. ∙ 56 ∙ share

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Phase-aware Speech Enhancement with Deep Complex U-Net

Most deep learning-based models for speech enhancement have mainly focus...
03/07/2019 ∙ by Hyeong-Seok Choi, et al. ∙ 0 ∙ share

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

Answerer in Questioner's Mind (AQM) is an information-theoretic framewor...
02/22/2019 ∙ by Sang-Woo Lee, et al. ∙ 0 ∙ share

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Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement

We present a hybrid framework that leverages the trade-off between tempo...
12/21/2018 ∙ by Jang-Hyun Kim, et al. ∙ 0 ∙ share

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

Many hyperparameter optimization (HyperOpt) methods assume restricted co...
10/08/2018 ∙ by Jinwoong Kim, et al. ∙ 0 ∙ share

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

The boom of deep learning induced many industries and academies to intro...
10/08/2018 ∙ by Hanjoo Kim, et al. ∙ 0 ∙ share

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Reinforcement Learning based Recommender System using Biclustering Technique

A recommender system aims to recommend items that a user is interested i...
01/17/2018 ∙ by Sungwoon Choi, et al. ∙ 0 ∙ share

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

Machine learning libraries such as TensorFlow and PyTorch simplify model...
12/16/2017 ∙ by Nako Sung, et al. ∙ 0 ∙ share

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Automatic Music Highlight Extraction using Convolutional Recurrent Attention Networks

Music highlights are valuable contents for music services. Most methods ...
12/16/2017 ∙ by Jung-Woo Ha, et al. ∙ 0 ∙ share

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Highrisk Prediction from Electronic Medical Records via Deep Attention Networks

Predicting highrisk vascular diseases is a significant issue in the medi...
11/30/2017 ∙ by You Jin Kim, et al. ∙ 0 ∙ share

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

Recent studies have shown remarkable success in image-to-image translati...
11/24/2017 ∙ by Yunjey Choi, et al. ∙ 0 ∙ share

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Representation Learning of Music Using Artist Labels

Recently, feature representation by learning algorithms has drawn great ...
10/18/2017 ∙ by Jiyoung Park, et al. ∙ 0 ∙ share

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

Recommender systems aim to find an accurate and efficient mapping from h...
06/28/2017 ∙ by Jaeyoon Yoo, et al. ∙ 0 ∙ share

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Dual Attention Networks for Multimodal Reasoning and Matching

We propose Dual Attention Networks (DANs) which jointly leverage visual ...
11/02/2016 ∙ by Hyeonseob Nam, et al. ∙ 0 ∙ share

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Hadamard Product for Low-rank Bilinear Pooling

Bilinear models provide rich representations compared with linear models...
10/14/2016 ∙ by Jin-Hwa Kim, et al. ∙ 0 ∙ share

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Multimodal Residual Learning for Visual QA

Deep neural networks continue to advance the state-of-the-art of image r...
06/05/2016 ∙ by Jin-Hwa Kim, et al. ∙ 0 ∙ share

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Jung-Woo Ha

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