Romanian Style Chinese Modern Poetry Generation with Pre-Trained Model and Direct Preference Optimization

The poetry of distant country with different culture and language is always distinctive and fascinating. Chinese and Romanian belong to Sinitic languages of the Sino-Tibetan language family and Romance languages of the Indo-European language family, which have relatively different syntax and general imagery of literature. Therefore, in this study, we make an attempt that was rarely involved in previous poetry generation research, using modern Chinese as the carrier, and generating modern poetry with Romanian style based on pre-trained model and direct preference optimization. Using a 5-point grading system, human evaluators awarded scores ranging from 3.21 to 3.83 across seven evaluation perspectives for the generated poems, achieving 76.2% to 91.6% of the comparable scores for the Chinese translations of authentic Romanian poems. The coincidence of the 30th to the 50th most frequently occurring poetic images in both generated poems and Romanian poems can reach 58.0–63.3%. Human evaluation and comparative statistical results on poetic imagery show that direct preference optimization is of great help in improving the degree of stylization, and the model can successfully create Chinese modern poems with Romanian style.