177 citations · 189 across the 12 of their papers we have counts for
5 papers · 1 filter
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…
PePe: Personalized Post-editing Model utilizing User-generated Post-edits
Jihyeon Lee, Taehee Kim, Yunwon Tae +2
Incorporating personal preference is crucial in advanced machine translation tasks. Despite the recent advancement of machine translation, it remains a demanding task to properly r…
A Visual Analytics System for Improving Attention-based Traffic Forecasting Models
Seungmin Jin, Hyunwook Lee, Cheonbok Park +4
With deep learning (DL) outperforming conventional methods for different tasks, much effort has been devoted to utilizing DL in various domains. Researchers and developers in the 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…