Intelligent Translation Workflow: Small Model Translation with Large Model Review

This diagram illustrates an intelligent translation workflow featuring "small model translation and large model review." The process begins with project creation and source material acquisition, followed by an initial translation generated by a small model. A quality assessment ensues: if the output meets standards, a standard initial draft is produced; otherwise, the text undergoes a refinement phase. The core of the system lies in the large model (DeepSeek) polishing stage, which integrates contextual elements—such as project-specific system prompts, full-text information, and translation memory—to generate a polished translation. Finally, the text undergoes another quality assessment; if it passes, the final draft is generated, whereas any remaining issues trigger a loop back to the polishing stage for further iteration. This approach leverages the large model's deep comprehension capabilities to significantly enhance the accuracy of the small model's initial translation.