View Translation
View translation encompasses the automated conversion of information between different modalities (e.g., text, speech, images, sign language) and languages, aiming to bridge communication gaps across diverse forms of expression. Current research emphasizes improving translation accuracy and efficiency using large language models (LLMs), exploring techniques like contrastive preference optimization, attention mechanism refinements, and multi-source pivoting, often within specific architectures such as transformers and Conformers. This field is crucial for advancing multilingual natural language processing, enabling broader access to information and facilitating cross-cultural communication in various applications, including healthcare, education, and cybersecurity.
Papers
Multilingual Pixel Representations for Translation and Effective Cross-lingual Transfer
Elizabeth Salesky, Neha Verma, Philipp Koehn, Matt Post
LIMIT: Language Identification, Misidentification, and Translation using Hierarchical Models in 350+ Languages
Milind Agarwal, Md Mahfuz Ibn Alam, Antonios Anastasopoulos
Translation and Fusion Improves Zero-shot Cross-lingual Information Extraction
Yang Chen, Vedaant Shah, Alan Ritter