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Found 10 papers, 1 papers with code
FeatureBART: Feature Based Sequence-to-Sequence Pre-Training for Low-Resource NMT
In this paper we present FeatureBART, a linguistically motivated sequence-to-sequence monolingual pre-training strategy in which syntactic features such as lemma, part-of-speech and dependency labels are incorporated into the span prediction based pre-training framework (BART).
Field Experiments of Real Time Foreign News Distribution Powered by MT
The second technology is machine translation (MT), which enables users to read foreign news articles in their mother language.
Neural Machine Translation Using Extracted Context Based on Deep Analysis for the Japanese-English Newswire Task at WAT 2020
This paper describes the system of the NHK-NES team for the WAT 2020 Japanese–English newswire task.
Centroid-Based Efficient Minimum Bayes Risk Decoding
Minimum Bayes risk (MBR) decoding achieved state-of-the-art translation performance by using COMET, a neural metric that has a high correlation with human evaluation.
SciCap+: A Knowledge Augmented Dataset to Study the Challenges of Scientific Figure Captioning
Automating figure caption generation helps move model understandings of scientific documents beyond text and will help authors write informative captions that facilitate communicating scientific findings.
Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT
The first problem is the quality of parallel corpora.
Neural Machine Translation System using a Content-equivalently Translated Parallel Corpus for the Newswire Translation Tasks at WAT 2019
The content-equivalent corpus was effective for improving translation quality, and our systems achieved the best human evaluation scores in the newswire translation tasks at WAT 2019.
Detecting Untranslated Content for Neural Machine Translation
Despite its promise, neural machine translation (NMT) has a serious problem in that source content may be mistakenly left untranslated.
