Zobrazeno 1 - 10
of 510
pro vyhledávání: '"Multimodal machine translation"'
Visual information has been introduced for enhancing machine translation (MT), and its effectiveness heavily relies on the availability of large amounts of bilingual parallel sentence pairs with manual image annotations. In this paper, we introduce a
Externí odkaz:
http://arxiv.org/abs/2412.12627
Current multimodal machine translation (MMT) systems rely on fully supervised data (i.e models are trained on sentences with their translations and accompanying images). However, this type of data is costly to collect, limiting the extension of MMT t
Externí odkaz:
http://arxiv.org/abs/2407.13579
Autor:
Żelasko, Piotr, Chen, Zhehuai, Wang, Mengru, Galvez, Daniel, Hrinchuk, Oleksii, Ding, Shuoyang, Hu, Ke, Balam, Jagadeesh, Lavrukhin, Vitaly, Ginsburg, Boris
A rising interest in the modality extension of foundation language models warrants discussion on the most effective, and efficient, multimodal training approach. This work focuses on neural machine translation (NMT) and proposes a joint multimodal tr
Externí odkaz:
http://arxiv.org/abs/2409.13523
Recent research in the field of multimodal machine translation (MMT) has indicated that the visual modality is either dispensable or offers only marginal advantages. However, most of these conclusions are drawn from the analysis of experimental resul
Externí odkaz:
http://arxiv.org/abs/2404.06107
The challenge of visual grounding and masking in multimodal machine translation (MMT) systems has encouraged varying approaches to the detection and selection of visually-grounded text tokens for masking. We introduce new methods for detection of vis
Externí odkaz:
http://arxiv.org/abs/2403.03075
Publikováno v:
Journal of Universal Computer Science, Vol 30, Iss 5, Pp 694-717 (2024)
Multimodal machine translation (MMT) is a challenging task in the linguistically diverse Indian landscape. Machine translation refers to the task of automatically converting content from one language to another without human involvement. Within the r
Externí odkaz:
https://doaj.org/article/893589a7175c4d728a35f232f615ea47
Existing multimodal machine translation (MMT) datasets consist of images and video captions or instructional video subtitles, which rarely contain linguistic ambiguity, making visual information ineffective in generating appropriate translations. Rec
Externí odkaz:
http://arxiv.org/abs/2310.20201
This paper presents an in-depth study of multimodal machine translation (MMT), examining the prevailing understanding that MMT systems exhibit decreased sensitivity to visual information when text inputs are complete. Instead, we attribute this pheno
Externí odkaz:
http://arxiv.org/abs/2310.17133
Multimodal machine translation (MMT) simultaneously takes the source sentence and a relevant image as input for translation. Since there is no paired image available for the input sentence in most cases, recent studies suggest utilizing powerful text
Externí odkaz:
http://arxiv.org/abs/2310.13361
Akademický článek
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