10 citations · 11 across the 3 of their papers we have counts for
5 papers
Specializing Multi-domain NMT via Penalizing Low Mutual Information
Jiyoung Lee, Hantae Kim, Hyunchang Cho +2
Multi-domain Neural Machine Translation (NMT) trains a single model with multiple domains. It is appealing because of its efficacy in handling multiple domains within one model. An…
Residual Correction in Real-Time Traffic Forecasting
Daejin Kim, Youngin Cho, Dongmin Kim +2
Predicting traffic conditions is tremendously challenging since every road is highly dependent on each other, both spatially and temporally. Recently, to capture this spatial and t…
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation
Cheonbok Park, Hantae Kim, Ioan Calapodescu +2
Domain Adaptation (DA) of Neural Machine Translation (NMT) model often relies on a pre-trained general NMT model which is adapted to the new domain on a sample of in-domain paralle…
ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed
Cheonbok Park, Chunggi Lee, Hyojin Bahng +5
Predicting road traffic speed is a challenging task due to different types of roads, abrupt speed change and spatial dependencies between roads; it requires the modeling of dynamic…
SANVis: Visual Analytics for Understanding Self-Attention Networks
Cheonbok Park, Inyoup Na, Yongjang Jo +7
Attention networks, a deep neural network architecture inspired by humans' attention mechanism, have seen significant success in image captioning, machine translation, and many oth…