Download PDFOpen PDF in browserCurrent versionEnhancing Cross-Lingual Understanding: Innovations in Machine TranslationEasyChair Preprint 12206, version 16 pages•Date: February 20, 2024AbstractThis paper explores recent innovations in MT, focusing on advancements aimed at enhancing the accuracy, fluency, and contextuality of translations. The abstract begins by contextualizing the importance of cross-lingual understanding in today's globalized society. It highlights the pivotal role of Machine Translation (MT) in bridging linguistic barriers and facilitating effective communication across diverse cultures and languages. The abstract then provides an overview of the primary focus of the paper: recent innovations in MT. It emphasizes advancements that target improving the accuracy, fluency, and contextuality of translations. These innovations encompass various approaches, including neural machine translation, transfer learning, and leveraging large-scale pre-trained models. Keyphrases: PRE, models, trained
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