Zobrazeno 1 - 10
of 4 415 369
pro vyhledávání: '"An MT"'
Publikováno v:
MT Hojgaard A/S MarketLine Company Profile. 12/1/2023, p1-13. 13p.
Publikováno v:
Progress in Modern Biomedicine. 2024, Vol. 24 Issue 17, p3381-3385. 5p.
Autor:
Li, Lei1 (AUTHOR) zheyilee@126.com, Shao, Chenshan2 (AUTHOR) lvlinlan77@126.com, Xv, Guodong1 (AUTHOR) xuguodong1028@163.com, Lv, Linlan2 (AUTHOR), Jiang, Jiacheng2 (AUTHOR), Zou, Weiyi2 (AUTHOR), Su, Weiwei2 (AUTHOR), Sui, Yanming2 (AUTHOR) suiyanming@foxmail.com, Jiang, Mei1 (AUTHOR) suiyanming@foxmail.com
Publikováno v:
Fishes (MDPI AG). Oct2024, Vol. 9 Issue 10, p407. 8p.
Publikováno v:
MT Hojgaard A/S MarketLine Company Profile. 11/30/2022, p1-13. 13p.
Recent Large Language Models (LLMs) have demonstrated strong performance in translation without needing to be finetuned on additional parallel corpora. However, they still underperform for low-resource language pairs. Previous works have focused on m
Externí odkaz:
http://arxiv.org/abs/2410.11693
This paper describes NLIP Lab's multilingual machine translation system for the WAT24 shared task on multilingual Indic MT task for 22 scheduled languages belonging to 4 language families. We explore pre-training for Indic languages using alignment a
Externí odkaz:
http://arxiv.org/abs/2410.13443
Autor:
Bakken-French, Nicolas1 (AUTHOR) nicolas.bakkenfrench@gmail.com, Boyer, Stephen J.1 (AUTHOR), Southworth, B. Clay1 (AUTHOR), Thayne, Megan1 (AUTHOR), Rood, Dylan H.2 (AUTHOR) d.rood@imperial.ac.uk, Carlson, Anders E.1 (AUTHOR)
Publikováno v:
Cryosphere. 2024, Vol. 18 Issue 9, p4517-4530. 14p.
We present MetaMetrics-MT, an innovative metric designed to evaluate machine translation (MT) tasks by aligning closely with human preferences through Bayesian optimization with Gaussian Processes. MetaMetrics-MT enhances existing MT metrics by optim
Externí odkaz:
http://arxiv.org/abs/2411.00390
Autor:
Lankford, Séamus, Way, Andy
In an evolving landscape of crisis communication, the need for robust and adaptable Machine Translation (MT) systems is more pressing than ever, particularly for low-resource languages. This study presents a comprehensive exploration of leveraging La
Externí odkaz:
http://arxiv.org/abs/2410.23890
In this paper, we describe our system for the WMT 24 shared task of Low-Resource Indic Language Translation. We consider eng $\leftrightarrow$ {as, kha, lus, mni} as participating language pairs. In this shared task, we explore the finetuning of a pr
Externí odkaz:
http://arxiv.org/abs/2410.03215