@inproceedings{jiangkuo-etal-2024-chinese,
    title = "{C}hinese Vision-Language Understanding Evaluation",
    author = "Wang, Jiangkuo  and
      Zheng, Linwei  and
      Chen, Kehai  and
      Bai, Xuefeng  and
      Zhang, Min",
    editor = "Hongfei, Lin  and
      Hongye, Tan  and
      Bin, Li",
    booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)",
    month = jul,
    year = "2024",
    address = "Taiyuan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/corrections-2025-09/2024.ccl-3.41/",
    pages = "363--373",
    language = "eng",
    abstract = "``This paper introduces our systems submitted for the Chinese Vision-Language Understanding Evaluation task at the 23rd Chinese Computational Linguistics Conference.In this competition, we utilized X2-VLM and CCLM models to participate in various subtasks such as image-text retrieval, visual grounding, visual dialogue, and visual question answering. Additionally, we employed other models to assess performance on certain subtasks. We optimized our models and successfully applied them to these different tasks''"
}