Research on human–machine collaborative academic English translation paths driven by generative artificial intelligence

Vollständiger Abstract

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Generative Artificial Intelligence (GenAI), with its powerful corpus-processing and rapid text-generation capabilities, has been widely applied in the field of translation, bringing new momentum to academic English translation. Human–machine collaborative translation based on Large Language Models (LLMs) can substantially improve the efficiency of academic English translation and play an important role in supporting international academic publication, communication at international conferences, and the dissemination of academic discourse internationally. However, GenAI also has inherent limitations in handling complex academic logic and constructing discourse for cross-cultural communication. Therefore, exploring human–machine collaborative approaches to academic English translation driven by GenAI is of considerable significance for effectively improving the quality and efficiency of academic English translation. Accordingly, this study analyzes the characteristics of academic English translation, as well as the advantages and limitations of applying GenAI to academic English translation, and proposes pathways for human–machine collaborative academic English translation driven by GenAI, with the aim of providing practical guidance for academic English translation.