research
∙
06/21/2023
Towards Accurate Translation via Semantically Appropriate Application of Lexical Constraints
Lexically-constrained NMT (LNMT) aims to incorporate user-provided termi...
share
research
∙
10/24/2022
Specializing Multi-domain NMT via Penalizing Low Mutual Information
Multi-domain Neural Machine Translation (NMT) trains a single model with...
research
∙
09/21/2022
PePe: Personalized Post-editing Model utilizing User-generated Post-edits
Incorporating personal preference is crucial in advanced machine transla...
research
∙
09/12/2022
Residual Correction in Real-Time Traffic Forecasting
Predicting traffic conditions is tremendously challenging since every ro...
research
∙
08/08/2022
A Visual Analytics System for Improving Attention-based Traffic Forecasting Models
With deep learning (DL) outperforming conventional methods for different...
research
∙
04/20/2022
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation
Domain Adaptation (DA) of Neural Machine Translation (NMT) model often r...
research
∙
05/12/2021
An Empirical Experiment on Deep Learning Models for Predicting Traffic Data
To tackle ever-increasing city traffic congestion problems, researchers ...
research
∙
10/18/2020
Meta-Learning for Low-Resource Unsupervised Neural MachineTranslation
Unsupervised machine translation, which utilizes unpaired monolingual co...
research
∙
11/29/2019
STGRAT: A Spatio-Temporal Graph Attention Network for Traffic Forecasting
Predicting the road traffic speed is a challenging task due to different...
research
∙
09/13/2019