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1
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
In: https://hal.inria.fr/hal-03177623 ; 2021 (2021)
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2
A Large-Scale Study of Machine Translation in the Turkic Languages ...
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3
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets ...
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4
Evaluating Multiway Multilingual NMT in the Turkic Languages ...
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5
Vision Matters When It Should: Sanity Checking Multimodal Machine Translation Models ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.673/ Abstract: Multimodal machine translation (MMT) systems have been shown to outperform their text-only neural machine translation (NMT) counterparts when visual context is available. However, recent studies have also shown that the performance of MMT models is only marginally impacted when the associated image is replaced with an unrelated image or noise, which suggests that the visual context might not be exploited by the model at all. We hypothesize that this might be caused by the nature of the commonly used evaluation benchmark, also known as Multi30K, where the translations of image captions were prepared without actually showing the images to human translators. In this paper, we present a qualitative study that examines the role of datasets in stimulating the leverage of visual modality and we propose methods to highlight the importance of visual signals in the datasets which demonstrate improvements in reliance of models on the source ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
URL: https://underline.io/lecture/37882-vision-matters-when-it-should-sanity-checking-multimodal-machine-translation-models
https://dx.doi.org/10.48448/4w38-v548
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