Neural machine translation: A review
F Stahlberg - Journal of Artificial Intelligence Research, 2020 - jair.org
The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …
natural language into another, has experienced a major paradigm shift in recent years …
Text summarization method based on double attention pointer network
A good document summary should summarize the core content of the text. Research on
automatic text summarization attempts to solve this problem. The encoder-decoder model is …
automatic text summarization attempts to solve this problem. The encoder-decoder model is …
As little as possible, as much as necessary: Detecting over-and undertranslations with contrastive conditioning
J Vamvas, R Sennrich - arXiv preprint arXiv:2203.01927, 2022 - arxiv.org
Omission and addition of content is a typical issue in neural machine translation. We
propose a method for detecting such phenomena with off-the-shelf translation models. Using …
propose a method for detecting such phenomena with off-the-shelf translation models. Using …
Dynamic past and future for neural machine translation
Previous studies have shown that neural machine translation (NMT) models can benefit from
explicitly modeling translated (Past) and untranslated (Future) to groups of translated and …
explicitly modeling translated (Past) and untranslated (Future) to groups of translated and …
Improving paragraph-level question generation with extended answer network and uncertainty-aware beam search
Question Generation (QG), which aims to generate a question given the relevant context, is
essential to build conversational and question–answering systems. Existing neural question …
essential to build conversational and question–answering systems. Existing neural question …
Restoring and mining the records of the Joseon dynasty via neural language modeling and machine translation
Understanding voluminous historical records provides clues on the past in various aspects,
such as social and political issues and even natural science facts. However, it is generally …
such as social and political issues and even natural science facts. However, it is generally …
Modeling future cost for neural machine translation
Existing neural machine translation (NMT) systems utilize sequence-to-sequence neural
networks to generate target translation word by word, and then make the generated word at …
networks to generate target translation word by word, and then make the generated word at …
Neural Machine Translation: A Review and Survey
F Stahlberg - arXiv preprint arXiv:1912.02047, 2019 - arxiv.org
The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …
natural language into another, has experienced a major paradigm shift in recent years …
A continuum of generation tasks for investigating length bias and degenerate repetition
Language models suffer from various degenerate behaviors. These differ between tasks:
machine translation (MT) exhibits length bias, while tasks like story generation exhibit …
machine translation (MT) exhibits length bias, while tasks like story generation exhibit …
Global-aware beam search for neural abstractive summarization
This study develops a calibrated beam-based algorithm with awareness of the global
attention distribution for neural abstractive summarization, aiming to improve the local …
attention distribution for neural abstractive summarization, aiming to improve the local …