2 citations · 5 across the 18 of their papers we have counts for
5 papers · 1 filter
A Self-Supervised Automatic Post-Editing Data Generation Tool
Hyeonseok Moon, Chanjun Park, Sugyeong Eo +3
Data building for automatic post-editing (APE) requires extensive and expert-level human effort, as it contains an elaborate process that involves identifying errors in sentences a…
A New Tool for Efficiently Generating Quality Estimation Datasets
Sugyeong Eo, Chanjun Park, Jaehyung Seo +2
Building of data for quality estimation (QE) training is expensive and requires significant human labor. In this study, we focus on a data-centric approach while performing QE, and…
Automatic Knowledge Augmentation for Generative Commonsense Reasoning
Jaehyung Seo, Chanjun Park, Sugyeong Eo +2
Generative commonsense reasoning is the capability of a language model to generate a sentence with a given concept-set that is based on commonsense knowledge. However, generative l…
How should human translation coexist with NMT? Efficient tool for building high quality parallel corpus
Chanjun Park, Seolhwa Lee, Hyeonseok Moon +3
This paper proposes a tool for efficiently constructing high-quality parallel corpora with minimizing human labor and making this tool publicly available. Our proposed construction…
Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC
Chanjun Park, Midan Shim, Sugyeong Eo +4
Machine translation (MT) system aims to translate source language into target language. Recent studies on MT systems mainly focus on neural machine translation (NMT). One factor th…