Comparative Study on the Translation Quality of "Three-Character Classic" by Large Language Models and Multimodal Large Models

With the widespread application of large language models (LLM) and multimodal large models (MLLM) in the field of machine translation, how to evaluate the translation quality of different models for ancient Chinese classics has become an urgent issue to be explored. This study takes the children's educational classic "Three Character Classic" as the research object, selects eight representative original sentences, and translates them into English using both LLM and MLLM. The translated texts are then quantitatively compared using the BLEU automatic evaluation tool. The aim of this study is to determine which type of model performs better in the English translation of classical Chinese texts and which model is more suitable for the translation tasks of Chinese classical literature. The study found that, here, fill in the actual experimental data: the BLEU and METEOR scores show which type of model performs better. This study provides empirical reference for AI-assisted English translation of Chinese ancient classics and also offers an empirical basis for the applicability of automatic translation quality assessment tools in the context of classical Chinese translation.