@inproceedings{wang-etal-2025-dutir914,
    title = "dutir914 at {S}em{E}val-2025 Task 1: An integrated approach for Multimodal Idiomaticity Representations",
    author = "Wang, Yanan  and
      Li, Dailin  and
      Tian, Yicen  and
      Zhang, Bo  and
      Jian, Wang  and
      Yang, Liang",
    editor = "Rosenthal, Sara  and
      Ros{\'a}, Aiala  and
      Ghosh, Debanjan  and
      Zampieri, Marcos",
    booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/transition-to-people-yaml/2025.semeval-1.159/",
    pages = "1198--1203",
    ISBN = "979-8-89176-273-2",
    abstract = "SemEval-2025 Task 1 introduces multimodal datasets for idiomatic expression representation. Subtask A focuses on ranking images based on potentially idiomatic noun compounds in given sentences. Idiom comprehension demands the fusion of visual and auditory elements with contextual semantics, yet existing datasets exhibit phrase-image discordance and culture-specific opacity, impeding cross-modal semantic alignment. To address these challenges, we propose an integrated approach that combines data augmentation and model fine-tuning in subtask A. First, we construct two idiom datasets by generating visual metaphors for idiomatic expressions to fine-tune the CLIP model. Next, We propose a three-stage multimodal chain-of-thought method, fine-tuning Qwen2.5-VL-7B-Instruct to generate rationales and perform inference, alongside zero-shot experiments with Qwen2.5-VL-72B-Instruct. Finally, we integrate the output of different models through a voting mechanism to enhance the accuracy of multimodal semantic matching. This approach achieves {\{}textbf{\{}0.92{\}}{\}} accuracy on the Portuguese test set and {\{}textbf{\{}0.93{\}}{\}} on the English test set, ranking {\{}textbf{\{}3rd{\}}{\}} and {\{}textbf{\{}4th{\}}{\}}, respectively. The implementation code is publicly available here{\{}footnote{\{}{\{}url{\{} https://github.com/wyn1015/semeval{\}}{\}}{\}}{\}}."
}