Chinese Vision-Language Understanding Evaluation

Jiangkuo Wang; Linwei Zheng; Kehai Chen (陈科海); Xuefeng Bai (白雪峰); Min Zhang

Chinese Vision-Language Understanding Evaluation

Jiangkuo Wang, Linwei Zheng, Kehai Chen, Xuefeng Bai, Min Zhang

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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”

Anthology ID:: 2024.ccl-3.41
Volume:: Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
Month:: July
Year:: 2024
Address:: Taiyuan, China
Editors:: Lin Hongfei, Tan Hongye, Li Bin
Venue:: CCL
SIG:
Publisher:: Chinese Information Processing Society of China
Note:
Pages:: 363–373
Language:: English
URL:: https://aclanthology.org/2024.ccl-3.41/
DOI:
Bibkey:
Cite (ACL):: Jiangkuo Wang, Linwei Zheng, Kehai Chen, Xuefeng Bai, and Min Zhang. 2024. Chinese Vision-Language Understanding Evaluation. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 363–373, Taiyuan, China. Chinese Information Processing Society of China.
Cite (Informal):: Chinese Vision-Language Understanding Evaluation (Wang et al., CCL 2024)
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PDF:: https://aclanthology.org/2024.ccl-3.41.pdf

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@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://aclanthology.org/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''"
}

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    <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”</abstract>
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%0 Conference Proceedings
%T Chinese Vision-Language Understanding Evaluation
%A Wang, Jiangkuo
%A Zheng, Linwei
%A Chen, Kehai
%A Bai, Xuefeng
%A Zhang, Min
%Y Hongfei, Lin
%Y Hongye, Tan
%Y Bin, Li
%S Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
%D 2024
%8 July
%I Chinese Information Processing Society of China
%C Taiyuan, China
%G eng
%F jiangkuo-etal-2024-chinese
%X “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”
%U https://aclanthology.org/2024.ccl-3.41/
%P 363-373

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Markdown (Informal)

[Chinese Vision-Language Understanding Evaluation](https://aclanthology.org/2024.ccl-3.41/) (Wang et al., CCL 2024)

Chinese Vision-Language Understanding Evaluation (Wang et al., CCL 2024)

ACL

Jiangkuo Wang, Linwei Zheng, Kehai Chen, Xuefeng Bai, and Min Zhang. 2024. Chinese Vision-Language Understanding Evaluation. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 363–373, Taiyuan, China. Chinese Information Processing Society of China.