Language Pair
Language pairs, representing the source and target languages in machine translation, are a central focus in natural language processing research, aiming to improve the accuracy and efficiency of cross-lingual communication. Current research emphasizes developing robust models, such as transformer-based architectures and retrieval-augmented methods, that address challenges like low-resource scenarios, data bias, and the need for diverse and high-quality translations. These advancements have significant implications for multilingual applications, including improved cross-lingual information access, enhanced accessibility of digital content, and the development of more inclusive and equitable technologies.
Papers
Decomposed Prompting for Machine Translation Between Related Languages using Large Language Models
Ratish Puduppully, Anoop Kunchukuttan, Raj Dabre, Ai Ti Aw, Nancy F. Chen
Mitigating Data Imbalance and Representation Degeneration in Multilingual Machine Translation
Wen Lai, Alexandra Chronopoulou, Alexander Fraser