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
Extending CREAMT: Leveraging Large Language Models for Literary Translation Post-Editing
Antonio Castaldo, Sheila Castilho, Joss Moorkens, Johanna MontiUniversity of Naples “L’Orientale”●University of Pisa●Dublin City UniversityTranslation of Fetal Brain Ultrasound Images into Pseudo-MRI Images using Artificial Intelligence
Naomi Silverstein, Efrat Leibowitz, Ron Beloosesky, Haim AzhariTechnion Institute of Technology●Rambam Health Care Campus
SpeechT: Findings of the First Mentorship in Speech Translation
Yasmin Moslem, Juan Julián Cea Morán, Mariano Gonzalez-Gomez, Muhammad Hazim Al Farouq, Farah Abdou, Satarupa DebGLoT: A Novel Gated-Logarithmic Transformer for Efficient Sign Language Translation
Nada Shahin, Leila IsmailEvaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis
Andong Chen, Yuchen Song, Wenxin Zhu, Kehai Chen, Muyun Yang, Tiejun Zhao, Min zhang