Scientific Development Research

Since 2003, applied translation studies in China have become a significant domain within translation research. With the increasing maturity of artificial intelligence (AI) technology, particularly the groundbreaking advancements in neural machine translation and large language models, applied translation and its research field are undergoing a profound paradigmatic shift. This paper aims to systematically examine and analyze the internal logic and pathway of the evolution of applied translation models from the elementary stage of "post-editing" to the advanced stage of "human-machine collaboration." It argues that this evolution signifies a transformation of translation activities from human-centered instrumental assistance to a symbiotic reconstruction characterized by deep integration of human and machine intelligence. The article first analyzes the structural limitations of the post-editing model, then explores the theoretical foundations and practical forms of the human-machine collaboration model. Finally, it elaborates on the core implications of reconstructing applied translation models across three dimensions: cognitive ecology, workflow, and translator competence. This study posits that human-machine collaboration represents not merely a technological progression but a systemic advancement in the intelligence, adaptability, and creativity of translation activities, offering a sustainable development path to meet the demands for massive volume, high quality, and rapid speed in translation within the era of globalization.

Applied translation; Artificial intelligence; Post-editing; Human-machine collaboration; Model reconstruction; Translator